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67  <div class="navpath"><b>itpp</b>::<a class="el" href="classitpp_1_1Convolutional__Code.html">Convolutional_Code</a>
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70<div class="contents">
71<h1>itpp::Convolutional_Code Class Reference<br>
72<small>
73[<a class="el" href="group__fec.html">Forward Error Correcting Codes</a>]</small>
74</h1><!-- doxytag: class="itpp::Convolutional_Code" --><!-- doxytag: inherits="itpp::Channel_Code" -->Binary Convolutional rate 1/n class. 
75<a href="#_details">More...</a>
76<p>
77<code>#include &lt;<a class="el" href="convcode_8h-source.html">convcode.h</a>&gt;</code>
78<p>
79
80<p>
81<a href="classitpp_1_1Convolutional__Code-members.html">List of all members.</a><table border="0" cellpadding="0" cellspacing="0">
82<tr><td></td></tr>
83<tr><td colspan="2"><br><h2>Public Member Functions</h2></td></tr>
84<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="7fa593431fe01986a69247a493d88bae"></a><!-- doxytag: member="itpp::Convolutional_Code::Convolutional_Code" ref="7fa593431fe01986a69247a493d88bae" args="(void)" -->
85&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#7fa593431fe01986a69247a493d88bae">Convolutional_Code</a> (void)</td></tr>
86
87<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Default constructor - sets (0133,0171) code with tail. <br></td></tr>
88<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="7e2a367b256e504f8c229afa677d8d23"></a><!-- doxytag: member="itpp::Convolutional_Code::~Convolutional_Code" ref="7e2a367b256e504f8c229afa677d8d23" args="(void)" -->
89virtual&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#7e2a367b256e504f8c229afa677d8d23">~Convolutional_Code</a> (void)</td></tr>
90
91<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Destructor. <br></td></tr>
92<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="1c49283f24dddf4e8cee2835f9d26afe"></a><!-- doxytag: member="itpp::Convolutional_Code::set_method" ref="1c49283f24dddf4e8cee2835f9d26afe" args="(const CONVOLUTIONAL_CODE_METHOD method)" -->
93void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#1c49283f24dddf4e8cee2835f9d26afe">set_method</a> (const <a class="el" href="group__fec.html#ge22fe2744a6f00b512ee75e304d72a82">CONVOLUTIONAL_CODE_METHOD</a> method)</td></tr>
94
95<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Set encoding and decoding method (Trunc, Tail, or Tailbite). <br></td></tr>
96<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#9860c6e22e6f7a58c020534045a432d0">set_code</a> (const <a class="el" href="group__fec.html#ge9651aa649deec69310af24cd89b8729">CONVOLUTIONAL_CODE_TYPE</a> type_of_code, int inverse_rate, int constraint_length)</td></tr>
97
98<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Set the code according to built-in tables.  <a href="#9860c6e22e6f7a58c020534045a432d0"></a><br></td></tr>
99<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="b8ca18ab14b3b6a1e1a1132f0386c84f"></a><!-- doxytag: member="itpp::Convolutional_Code::set_generator_polynomials" ref="b8ca18ab14b3b6a1e1a1132f0386c84f" args="(const ivec &amp;gen, int constraint_length)" -->
100void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#b8ca18ab14b3b6a1e1a1132f0386c84f">set_generator_polynomials</a> (const ivec &amp;gen, int constraint_length)</td></tr>
101
102<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Set generator polynomials. Given in Proakis integer form. <br></td></tr>
103<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="342e071696583197507b85fb45146bc6"></a><!-- doxytag: member="itpp::Convolutional_Code::get_generator_polynomials" ref="342e071696583197507b85fb45146bc6" args="(void) const " -->
104ivec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#342e071696583197507b85fb45146bc6">get_generator_polynomials</a> (void) const </td></tr>
105
106<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get generator polynomials. <br></td></tr>
107<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="6ac83f0a1be7b4f6f06a1b4d7b45489a"></a><!-- doxytag: member="itpp::Convolutional_Code::reset" ref="6ac83f0a1be7b4f6f06a1b4d7b45489a" args="()" -->
108void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#6ac83f0a1be7b4f6f06a1b4d7b45489a">reset</a> ()</td></tr>
109
110<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Reset encoder and decoder states. <br></td></tr>
111<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="f3bf2206a471342563a4080e42d6b435"></a><!-- doxytag: member="itpp::Convolutional_Code::decode" ref="f3bf2206a471342563a4080e42d6b435" args="(const bvec &amp;coded_bits, bvec &amp;decoded_bits)" -->
112virtual void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#f3bf2206a471342563a4080e42d6b435">decode</a> (const bvec &amp;coded_bits, bvec &amp;decoded_bits)</td></tr>
113
114<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Decode a bvec of coded data. <br></td></tr>
115<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="59ade7649db617d9ad30401342075cb7"></a><!-- doxytag: member="itpp::Convolutional_Code::decode" ref="59ade7649db617d9ad30401342075cb7" args="(const bvec &amp;coded_bits)" -->
116virtual bvec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#59ade7649db617d9ad30401342075cb7">decode</a> (const bvec &amp;coded_bits)</td></tr>
117
118<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Decode a bvec of coded data. <br></td></tr>
119<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="e7e892230d677d7b64917cd6f8e7b823"></a><!-- doxytag: member="itpp::Convolutional_Code::get_rate" ref="e7e892230d677d7b64917cd6f8e7b823" args="(void) const " -->
120virtual double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#e7e892230d677d7b64917cd6f8e7b823">get_rate</a> (void) const </td></tr>
121
122<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Return rate of code (not including the rate-loss). <br></td></tr>
123<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="6316d7d75c01471aa44d533fdaa586c1"></a><!-- doxytag: member="itpp::Convolutional_Code::set_start_state" ref="6316d7d75c01471aa44d533fdaa586c1" args="(int state)" -->
124void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#6316d7d75c01471aa44d533fdaa586c1">set_start_state</a> (int state)</td></tr>
125
126<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Set encoder default start state. <br></td></tr>
127<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="9ef6fc1934531d3c12123ed90c5b4c40"></a><!-- doxytag: member="itpp::Convolutional_Code::init_encoder" ref="9ef6fc1934531d3c12123ed90c5b4c40" args="()" -->
128void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#9ef6fc1934531d3c12123ed90c5b4c40">init_encoder</a> ()</td></tr>
129
130<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Initialise internal encoder state with start state. Has no effect on <code>Tail</code> and <code>Tailbite</code> methods. <br></td></tr>
131<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="22321baddd7afddcd255356debaf0fb8"></a><!-- doxytag: member="itpp::Convolutional_Code::get_encoder_state" ref="22321baddd7afddcd255356debaf0fb8" args="(void) const " -->
132int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#22321baddd7afddcd255356debaf0fb8">get_encoder_state</a> (void) const </td></tr>
133
134<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get the current encoder state. <br></td></tr>
135<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="a1929841dfb95d406fa1a16867f144bb"></a><!-- doxytag: member="itpp::Convolutional_Code::set_truncation_length" ref="a1929841dfb95d406fa1a16867f144bb" args="(const int length)" -->
136void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#a1929841dfb95d406fa1a16867f144bb">set_truncation_length</a> (const int length)</td></tr>
137
138<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Set memory truncation length. Must be at least K. <br></td></tr>
139<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="35d7ef525f88707e4ff2c6ed05469c00"></a><!-- doxytag: member="itpp::Convolutional_Code::get_truncation_length" ref="35d7ef525f88707e4ff2c6ed05469c00" args="(void) const " -->
140int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#35d7ef525f88707e4ff2c6ed05469c00">get_truncation_length</a> (void) const </td></tr>
141
142<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Get memory truncation length. <br></td></tr>
143<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="7fbeb36821dcd85d981ae99bc106cba8"></a><!-- doxytag: member="itpp::Convolutional_Code::catastrophic" ref="7fbeb36821dcd85d981ae99bc106cba8" args="(void)" -->
144bool&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#7fbeb36821dcd85d981ae99bc106cba8">catastrophic</a> (void)</td></tr>
145
146<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Check if catastrophic. Returns true if catastrophic. <br></td></tr>
147<tr><td class="memItemLeft" nowrap align="right" valign="top">bool&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#635406cac085c188709234c688ce2c68">inverse_tail</a> (const bvec coded_sequence, bvec &amp;input)</td></tr>
148
149<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Calculate the inverse sequence.  <a href="#635406cac085c188709234c688ce2c68"></a><br></td></tr>
150<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="e99bf2f2d1973c7626214ad93222cbcf"></a><!-- doxytag: member="itpp::Convolutional_Code::distance_profile" ref="e99bf2f2d1973c7626214ad93222cbcf" args="(ivec &amp;dist_prof, int dmax=100000, bool reverse=false)" -->
151void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#e99bf2f2d1973c7626214ad93222cbcf">distance_profile</a> (ivec &amp;dist_prof, int dmax=100000, bool reverse=false)</td></tr>
152
153<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Calculate distance profile. If reverse = true calculate for the reverse code instead. <br></td></tr>
154<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#3f442fd4218c746dc046ea996f301cf7">calculate_spectrum</a> (<a class="el" href="classitpp_1_1Array.html">Array</a>&lt; ivec &gt; &amp;spectrum, int dmax, int no_terms)</td></tr>
155
156<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Calculate spectrum.  <a href="#3f442fd4218c746dc046ea996f301cf7"></a><br></td></tr>
157<tr><td class="memItemLeft" nowrap align="right" valign="top">int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#8217a8922992b1fb4faa28d86f21e6d7">fast</a> (<a class="el" href="classitpp_1_1Array.html">Array</a>&lt; ivec &gt; &amp;spectrum, const int dfree, const int no_terms, const int Cdfree=1000000, const bool test_catastrophic=false)</td></tr>
158
159<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Cederwall's fast algorithm.  <a href="#8217a8922992b1fb4faa28d86f21e6d7"></a><br></td></tr>
160<tr><td colspan="2"><div class="groupHeader"></div></td></tr>
161<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="f9d5354b5ea7f2a090a488b383e995ef"></a><!-- doxytag: member="itpp::Convolutional_Code::encode" ref="f9d5354b5ea7f2a090a488b383e995ef" args="(const bvec &amp;input, bvec &amp;output)" -->
162virtual void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#f9d5354b5ea7f2a090a488b383e995ef">encode</a> (const bvec &amp;input, bvec &amp;output)</td></tr>
163
164<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Encode an input binary vector using specified method (Tail by default). <br></td></tr>
165<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="fbed8d23cbffca2d0802234592b034b4"></a><!-- doxytag: member="itpp::Convolutional_Code::encode" ref="fbed8d23cbffca2d0802234592b034b4" args="(const bvec &amp;input)" -->
166virtual bvec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#fbed8d23cbffca2d0802234592b034b4">encode</a> (const bvec &amp;input)</td></tr>
167
168<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Encode a bvec of input. <br></td></tr>
169<tr><td colspan="2"><div class="groupHeader"></div></td></tr>
170<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#b2acc3b632782ff035fa1b5b2b122153">encode_trunc</a> (const bvec &amp;input, bvec &amp;output)</td></tr>
171
172<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Encode a binary vector starting from the previous encoder state.  <a href="#b2acc3b632782ff035fa1b5b2b122153"></a><br></td></tr>
173<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="8e17b5077deeb8fea1bc2a617a7d92e6"></a><!-- doxytag: member="itpp::Convolutional_Code::encode_trunc" ref="8e17b5077deeb8fea1bc2a617a7d92e6" args="(const bvec &amp;input)" -->
174bvec&nbsp;</td><td class="memItemRight" valign="bottom"><b>encode_trunc</b> (const bvec &amp;input)</td></tr>
175
176<tr><td colspan="2"><div class="groupHeader"></div></td></tr>
177<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#47230acfea5aa32cb31e63abca1d222e">encode_tail</a> (const bvec &amp;input, bvec &amp;output)</td></tr>
178
179<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Encoding that starts and ends in the zero state.  <a href="#47230acfea5aa32cb31e63abca1d222e"></a><br></td></tr>
180<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="b6e95d4835d7e783ed6f46f2f2ca710d"></a><!-- doxytag: member="itpp::Convolutional_Code::encode_tail" ref="b6e95d4835d7e783ed6f46f2f2ca710d" args="(const bvec &amp;input)" -->
181bvec&nbsp;</td><td class="memItemRight" valign="bottom"><b>encode_tail</b> (const bvec &amp;input)</td></tr>
182
183<tr><td colspan="2"><div class="groupHeader"></div></td></tr>
184<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#34e2691d01bc0b35d81f109f27bedfa2">encode_tailbite</a> (const bvec &amp;input, bvec &amp;output)</td></tr>
185
186<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Encode an input binary vector using tailbiting.  <a href="#34e2691d01bc0b35d81f109f27bedfa2"></a><br></td></tr>
187<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="0a37137eb369e9cd6208fa77f2462e98"></a><!-- doxytag: member="itpp::Convolutional_Code::encode_tailbite" ref="0a37137eb369e9cd6208fa77f2462e98" args="(const bvec &amp;input)" -->
188bvec&nbsp;</td><td class="memItemRight" valign="bottom"><b>encode_tailbite</b> (const bvec &amp;input)</td></tr>
189
190<tr><td colspan="2"><div class="groupHeader"></div></td></tr>
191<tr><td class="memItemLeft" nowrap align="right" valign="top">void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#a6884e3f60678177fbf60e22d2447a5b">encode_bit</a> (const <a class="el" href="classitpp_1_1bin.html">bin</a> &amp;input, bvec &amp;output)</td></tr>
192
193<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Encode a binary bit starting from the internal encoder state.  <a href="#a6884e3f60678177fbf60e22d2447a5b"></a><br></td></tr>
194<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="0c0c16ff8863936435a73f3e1efd9b99"></a><!-- doxytag: member="itpp::Convolutional_Code::encode_bit" ref="0c0c16ff8863936435a73f3e1efd9b99" args="(const bin &amp;input)" -->
195bvec&nbsp;</td><td class="memItemRight" valign="bottom"><b>encode_bit</b> (const <a class="el" href="classitpp_1_1bin.html">bin</a> &amp;input)</td></tr>
196
197<tr><td colspan="2"><div class="groupHeader"></div></td></tr>
198<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="cb932da00b3bb0e218175f180a770131"></a><!-- doxytag: member="itpp::Convolutional_Code::decode" ref="cb932da00b3bb0e218175f180a770131" args="(const vec &amp;received_signal, bvec &amp;output)" -->
199virtual void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#cb932da00b3bb0e218175f180a770131">decode</a> (const vec &amp;received_signal, bvec &amp;output)</td></tr>
200
201<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Decode a block of encoded data using specified method (Tail by default). <br></td></tr>
202<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="fbeada8e8cbeccdababfb26658faa02a"></a><!-- doxytag: member="itpp::Convolutional_Code::decode" ref="fbeada8e8cbeccdababfb26658faa02a" args="(const vec &amp;received_signal)" -->
203virtual bvec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#fbeada8e8cbeccdababfb26658faa02a">decode</a> (const vec &amp;received_signal)</td></tr>
204
205<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Decode a vec of received data. <br></td></tr>
206<tr><td colspan="2"><div class="groupHeader"></div></td></tr>
207<tr><td class="memItemLeft" nowrap align="right" valign="top">virtual void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#9f42d8c8bdb51460ebc7d43deb93bad7">decode_tail</a> (const vec &amp;received_signal, bvec &amp;output)</td></tr>
208
209<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Decode a block of encoded data where encode_tail has been used.  <a href="#9f42d8c8bdb51460ebc7d43deb93bad7"></a><br></td></tr>
210<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="6d4f0958fb739bbb86d2d969d8329ffb"></a><!-- doxytag: member="itpp::Convolutional_Code::decode_tail" ref="6d4f0958fb739bbb86d2d969d8329ffb" args="(const vec &amp;received_signal)" -->
211virtual bvec&nbsp;</td><td class="memItemRight" valign="bottom"><b>decode_tail</b> (const vec &amp;received_signal)</td></tr>
212
213<tr><td colspan="2"><div class="groupHeader"></div></td></tr>
214<tr><td class="memItemLeft" nowrap align="right" valign="top">virtual void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#94f2b7f77dc08fc0fb975735762be742">decode_tailbite</a> (const vec &amp;received_signal, bvec &amp;output)</td></tr>
215
216<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Decode a block of encoded data where encode_tailbite has been used.  <a href="#94f2b7f77dc08fc0fb975735762be742"></a><br></td></tr>
217<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="22a8f34f47de47a3dfa033efca3a6fd0"></a><!-- doxytag: member="itpp::Convolutional_Code::decode_tailbite" ref="22a8f34f47de47a3dfa033efca3a6fd0" args="(const vec &amp;received_signal)" -->
218virtual bvec&nbsp;</td><td class="memItemRight" valign="bottom"><b>decode_tailbite</b> (const vec &amp;received_signal)</td></tr>
219
220<tr><td colspan="2"><div class="groupHeader"></div></td></tr>
221<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="d92e8a3b194cc00bf29e060fb90b666a"></a><!-- doxytag: member="itpp::Convolutional_Code::decode_trunc" ref="d92e8a3b194cc00bf29e060fb90b666a" args="(const vec &amp;received_signal, bvec &amp;output)" -->
222virtual void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#d92e8a3b194cc00bf29e060fb90b666a">decode_trunc</a> (const vec &amp;received_signal, bvec &amp;output)</td></tr>
223
224<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Viterbi decoding using truncation of memory (default = 5*K). <br></td></tr>
225<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="d7e393ed6dccc03984b626ca6c3466df"></a><!-- doxytag: member="itpp::Convolutional_Code::decode_trunc" ref="d7e393ed6dccc03984b626ca6c3466df" args="(const vec &amp;received_signal)" -->
226virtual bvec&nbsp;</td><td class="memItemRight" valign="bottom"><b>decode_trunc</b> (const vec &amp;received_signal)</td></tr>
227
228<tr><td colspan="2"><br><h2>Protected Member Functions</h2></td></tr>
229<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="31df4741737f7b87b848ce95505f80fc"></a><!-- doxytag: member="itpp::Convolutional_Code::next_state" ref="31df4741737f7b87b848ce95505f80fc" args="(const int instate, const int input)" -->
230int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#31df4741737f7b87b848ce95505f80fc">next_state</a> (const int instate, const int input)</td></tr>
231
232<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Next state from instate given the input. <br></td></tr>
233<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="7bdfde49b386946dcd7476fbd2488dd8"></a><!-- doxytag: member="itpp::Convolutional_Code::previous_state" ref="7bdfde49b386946dcd7476fbd2488dd8" args="(const int state, const int input)" -->
234int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#7bdfde49b386946dcd7476fbd2488dd8">previous_state</a> (const int state, const int input)</td></tr>
235
236<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The previous state from state given the input. <br></td></tr>
237<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="681ad623bd14abcaabfa317d6fd0bdad"></a><!-- doxytag: member="itpp::Convolutional_Code::previous_state" ref="681ad623bd14abcaabfa317d6fd0bdad" args="(const int state, int &amp;S0, int &amp;S1)" -->
238void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#681ad623bd14abcaabfa317d6fd0bdad">previous_state</a> (const int state, int &amp;S0, int &amp;S1)</td></tr>
239
240<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The previous state from state given the input. <br></td></tr>
241<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="ceb3aadcb9da39f2330d5e9870bda5af"></a><!-- doxytag: member="itpp::Convolutional_Code::weight" ref="ceb3aadcb9da39f2330d5e9870bda5af" args="(const int state, const int input)" -->
242int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#ceb3aadcb9da39f2330d5e9870bda5af">weight</a> (const int state, const int input)</td></tr>
243
244<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The weight of the transition from given state with the input given. <br></td></tr>
245<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="7518410d14d05925f4e8a6de2655399a"></a><!-- doxytag: member="itpp::Convolutional_Code::weight" ref="7518410d14d05925f4e8a6de2655399a" args="(const int state, int &amp;w0, int &amp;w1)" -->
246void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#7518410d14d05925f4e8a6de2655399a">weight</a> (const int state, int &amp;w0, int &amp;w1)</td></tr>
247
248<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The weight of the two paths (input 0 or 1) from given state. <br></td></tr>
249<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="f600390d130ce3cb7aa2e33037560626"></a><!-- doxytag: member="itpp::Convolutional_Code::weight_reverse" ref="f600390d130ce3cb7aa2e33037560626" args="(const int state, const int input)" -->
250int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#f600390d130ce3cb7aa2e33037560626">weight_reverse</a> (const int state, const int input)</td></tr>
251
252<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The weight (of the reverse code) of the transition from given state with the input given. <br></td></tr>
253<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="2814b056af9cb40570aeaa39fc3f322f"></a><!-- doxytag: member="itpp::Convolutional_Code::weight_reverse" ref="2814b056af9cb40570aeaa39fc3f322f" args="(const int state, int &amp;w0, int &amp;w1)" -->
254void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#2814b056af9cb40570aeaa39fc3f322f">weight_reverse</a> (const int state, int &amp;w0, int &amp;w1)</td></tr>
255
256<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The weight (of the reverse code) of the two paths (input 0 or 1) from given state. <br></td></tr>
257<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="f286a1fb3897e5fd78e749b03aaadff6"></a><!-- doxytag: member="itpp::Convolutional_Code::output_reverse" ref="f286a1fb3897e5fd78e749b03aaadff6" args="(const int state, const int input)" -->
258bvec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#f286a1fb3897e5fd78e749b03aaadff6">output_reverse</a> (const int state, const int input)</td></tr>
259
260<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Output on transition (backwards) with input from state. <br></td></tr>
261<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="1780746970f5e9ffdddd26bc805e087d"></a><!-- doxytag: member="itpp::Convolutional_Code::output_reverse" ref="1780746970f5e9ffdddd26bc805e087d" args="(const int state, bvec &amp;zero_output, bvec &amp;one_output)" -->
262void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#1780746970f5e9ffdddd26bc805e087d">output_reverse</a> (const int state, bvec &amp;zero_output, bvec &amp;one_output)</td></tr>
263
264<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Output on transition (backwards) with input from state. <br></td></tr>
265<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="45d579da2009db6c0e7074c826ff96c2"></a><!-- doxytag: member="itpp::Convolutional_Code::output_reverse" ref="45d579da2009db6c0e7074c826ff96c2" args="(const int state, int &amp;zero_output, int &amp;one_output)" -->
266void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#45d579da2009db6c0e7074c826ff96c2">output_reverse</a> (const int state, int &amp;zero_output, int &amp;one_output)</td></tr>
267
268<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Output on transition (backwards) with input from state. <br></td></tr>
269<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="5860dd3376bf2b0971e8e2a45b755b04"></a><!-- doxytag: member="itpp::Convolutional_Code::calc_metric_reverse" ref="5860dd3376bf2b0971e8e2a45b755b04" args="(const int state, const vec &amp;rx_codeword, double &amp;zero_metric, double &amp;one_metric)" -->
270void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#5860dd3376bf2b0971e8e2a45b755b04">calc_metric_reverse</a> (const int state, const vec &amp;rx_codeword, double &amp;zero_metric, double &amp;one_metric)</td></tr>
271
272<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Calculate delta metrics for 0 and 1 input branches reaching state. <br></td></tr>
273<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="79f47928875683c5b2d91c50220ff3d6"></a><!-- doxytag: member="itpp::Convolutional_Code::calc_metric" ref="79f47928875683c5b2d91c50220ff3d6" args="(const vec &amp;rx_codeword, vec &amp;delta_metrics)" -->
274void&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#79f47928875683c5b2d91c50220ff3d6">calc_metric</a> (const vec &amp;rx_codeword, vec &amp;delta_metrics)</td></tr>
275
276<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Calculate delta metrics for all possible codewords. <br></td></tr>
277<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="028a1867c118c4fc5f8fea9b404bf20d"></a><!-- doxytag: member="itpp::Convolutional_Code::get_input" ref="028a1867c118c4fc5f8fea9b404bf20d" args="(const int state)" -->
278int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#028a1867c118c4fc5f8fea9b404bf20d">get_input</a> (const int state)</td></tr>
279
280<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Returns the input that results in state, that is the MSB of state. <br></td></tr>
281<tr><td colspan="2"><br><h2>Protected Attributes</h2></td></tr>
282<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="b314ab153e137a68c8a0ca6e1bbbdbee"></a><!-- doxytag: member="itpp::Convolutional_Code::n" ref="b314ab153e137a68c8a0ca6e1bbbdbee" args="" -->
283int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#b314ab153e137a68c8a0ca6e1bbbdbee">n</a></td></tr>
284
285<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Number of generators. <br></td></tr>
286<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="63430f36f9dc2c9d78b9a0ce145a8f2d"></a><!-- doxytag: member="itpp::Convolutional_Code::K" ref="63430f36f9dc2c9d78b9a0ce145a8f2d" args="" -->
287int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#63430f36f9dc2c9d78b9a0ce145a8f2d">K</a></td></tr>
288
289<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Constraint length. <br></td></tr>
290<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="b93371ece607184c04780de0e05d7abc"></a><!-- doxytag: member="itpp::Convolutional_Code::m" ref="b93371ece607184c04780de0e05d7abc" args="" -->
291int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#b93371ece607184c04780de0e05d7abc">m</a></td></tr>
292
293<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Memory of the encoder. <br></td></tr>
294<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="8c164aac0932007e5eeaa502d5bdb1ca"></a><!-- doxytag: member="itpp::Convolutional_Code::no_states" ref="8c164aac0932007e5eeaa502d5bdb1ca" args="" -->
295int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#8c164aac0932007e5eeaa502d5bdb1ca">no_states</a></td></tr>
296
297<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Number of states. <br></td></tr>
298<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="e5b54f1bab039f8480c7ae0013f3f5fe"></a><!-- doxytag: member="itpp::Convolutional_Code::gen_pol" ref="e5b54f1bab039f8480c7ae0013f3f5fe" args="" -->
299ivec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#e5b54f1bab039f8480c7ae0013f3f5fe">gen_pol</a></td></tr>
300
301<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Generator polynomials. <br></td></tr>
302<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="d072282520c19e64e8a88e0e79d91b96"></a><!-- doxytag: member="itpp::Convolutional_Code::gen_pol_rev" ref="d072282520c19e64e8a88e0e79d91b96" args="" -->
303ivec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#d072282520c19e64e8a88e0e79d91b96">gen_pol_rev</a></td></tr>
304
305<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Generator polynomials for the reverse code. <br></td></tr>
306<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="04a91848197a2624c5dbdbcd5224166a"></a><!-- doxytag: member="itpp::Convolutional_Code::encoder_state" ref="04a91848197a2624c5dbdbcd5224166a" args="" -->
307int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#04a91848197a2624c5dbdbcd5224166a">encoder_state</a></td></tr>
308
309<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The current encoder state. <br></td></tr>
310<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="7bfc69c7f70316fe051e2802c9f09ee3"></a><!-- doxytag: member="itpp::Convolutional_Code::start_state" ref="7bfc69c7f70316fe051e2802c9f09ee3" args="" -->
311int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#7bfc69c7f70316fe051e2802c9f09ee3">start_state</a></td></tr>
312
313<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The encoder start state. <br></td></tr>
314<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="57ef97ff464b7f36a284540426a26ce3"></a><!-- doxytag: member="itpp::Convolutional_Code::trunc_length" ref="57ef97ff464b7f36a284540426a26ce3" args="" -->
315int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#57ef97ff464b7f36a284540426a26ce3">trunc_length</a></td></tr>
316
317<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The decoder truncation length. <br></td></tr>
318<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="0e92407956851a04cffa5f89f2fd39a5"></a><!-- doxytag: member="itpp::Convolutional_Code::rate" ref="0e92407956851a04cffa5f89f2fd39a5" args="" -->
319double&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#0e92407956851a04cffa5f89f2fd39a5">rate</a></td></tr>
320
321<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">The rate of the code. <br></td></tr>
322<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="e31e1e09af8f51be5eb37ffca507d232"></a><!-- doxytag: member="itpp::Convolutional_Code::xor_int_table" ref="e31e1e09af8f51be5eb37ffca507d232" args="" -->
323bvec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#e31e1e09af8f51be5eb37ffca507d232">xor_int_table</a></td></tr>
324
325<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Auxilary table used by the codec. <br></td></tr>
326<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="7e63597801ab594d590234192eed3da4"></a><!-- doxytag: member="itpp::Convolutional_Code::output_reverse_int" ref="7e63597801ab594d590234192eed3da4" args="" -->
327imat&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#7e63597801ab594d590234192eed3da4">output_reverse_int</a></td></tr>
328
329<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">output in int format for a given state and input <br></td></tr>
330<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="df24ee075bc58e4b277c44cfd146d84b"></a><!-- doxytag: member="itpp::Convolutional_Code::cc_method" ref="df24ee075bc58e4b277c44cfd146d84b" args="" -->
331<a class="el" href="group__fec.html#ge22fe2744a6f00b512ee75e304d72a82">CONVOLUTIONAL_CODE_METHOD</a>&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#df24ee075bc58e4b277c44cfd146d84b">cc_method</a></td></tr>
332
333<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">encoding and decoding method <br></td></tr>
334<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="2be7d32bc57f8be15b9e45993d88253b"></a><!-- doxytag: member="itpp::Convolutional_Code::path_memory" ref="2be7d32bc57f8be15b9e45993d88253b" args="" -->
335imat&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#2be7d32bc57f8be15b9e45993d88253b">path_memory</a></td></tr>
336
337<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Path memory (trellis). <br></td></tr>
338<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="e840a45790781563ef45047652bf794b"></a><!-- doxytag: member="itpp::Convolutional_Code::visited_state" ref="e840a45790781563ef45047652bf794b" args="" -->
339<a class="el" href="classitpp_1_1Array.html">Array</a>&lt; bool &gt;&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#e840a45790781563ef45047652bf794b">visited_state</a></td></tr>
340
341<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Visited states. <br></td></tr>
342<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="2a894772cc027542c600f5b86fe17173"></a><!-- doxytag: member="itpp::Convolutional_Code::sum_metric" ref="2a894772cc027542c600f5b86fe17173" args="" -->
343vec&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#2a894772cc027542c600f5b86fe17173">sum_metric</a></td></tr>
344
345<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Metrics accumulator. <br></td></tr>
346<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="89b0d6ba21457e1aab73f53631a5cb7f"></a><!-- doxytag: member="itpp::Convolutional_Code::trunc_ptr" ref="89b0d6ba21457e1aab73f53631a5cb7f" args="" -->
347int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#89b0d6ba21457e1aab73f53631a5cb7f">trunc_ptr</a></td></tr>
348
349<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Truncated path memory pointer. <br></td></tr>
350<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="d26ed837b36f7313277a2b1dcc7b0c4c"></a><!-- doxytag: member="itpp::Convolutional_Code::trunc_state" ref="d26ed837b36f7313277a2b1dcc7b0c4c" args="" -->
351int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#d26ed837b36f7313277a2b1dcc7b0c4c">trunc_state</a></td></tr>
352
353<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Truncated memory fill state. <br></td></tr>
354<tr><td colspan="2"><br><h2>Related Functions</h2></td></tr>
355<tr><td colspan="2">(Note that these are not member functions.) <br><br></td></tr>
356<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="ca1881cee55d7c3219f46dd40e7cbd31"></a><!-- doxytag: member="itpp::Convolutional_Code::reverse_int" ref="ca1881cee55d7c3219f46dd40e7cbd31" args="(int length, int in)" -->
357int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#ca1881cee55d7c3219f46dd40e7cbd31">reverse_int</a> (int length, int in)</td></tr>
358
359<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Reverses the bitrepresentation of in (of size length) and converts to an integer. <br></td></tr>
360<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="33760fc0bdf27b4b5232694796590365"></a><!-- doxytag: member="itpp::Convolutional_Code::weight_int" ref="33760fc0bdf27b4b5232694796590365" args="(int length, int in)" -->
361int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#33760fc0bdf27b4b5232694796590365">weight_int</a> (int length, int in)</td></tr>
362
363<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Calculate the Hamming weight of the binary representation of in of size length. <br></td></tr>
364<tr><td class="memItemLeft" nowrap align="right" valign="top"><a class="anchor" name="9e332af5e8d1ce1ba795f4e032adace2"></a><!-- doxytag: member="itpp::Convolutional_Code::compare_spectra" ref="9e332af5e8d1ce1ba795f4e032adace2" args="(ivec v1, ivec v2)" -->
365int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#9e332af5e8d1ce1ba795f4e032adace2">compare_spectra</a> (ivec v1, ivec v2)</td></tr>
366
367<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Compare two distance spectra. Return 1 if v1 is less, 0 if v2 less, and -1 if equal. <br></td></tr>
368<tr><td class="memItemLeft" nowrap align="right" valign="top">int&nbsp;</td><td class="memItemRight" valign="bottom"><a class="el" href="classitpp_1_1Convolutional__Code.html#4abebe627013b4dfb5e1025c1f94c769">compare_spectra</a> (ivec v1, ivec v2, vec weight_profile)</td></tr>
369
370<tr><td class="mdescLeft">&nbsp;</td><td class="mdescRight">Compare two distance spectra using a weight profile.  <a href="#4abebe627013b4dfb5e1025c1f94c769"></a><br></td></tr>
371</table>
372<hr><a name="_details"></a><h2>Detailed Description</h2>
373Binary Convolutional rate 1/n class.
374<p>
375The codes are given as feedforward encoders and given in the Proakis form. That is, the binary generators (K-tuples) are converted to octal integers. Observe that the constraint length (K) is defined as the number of memory cells plus one (as in Proakis).<p>
376Encoding is performed with the encode function. The default method for encoding is by adding a tail of K-1 zeros and also assume that the encoder starts in the zero state (the <a class="el" href="classitpp_1_1Convolutional__Code.html#47230acfea5aa32cb31e63abca1d222e" title="Encoding that starts and ends in the zero state.">encode_tail()</a> function). Observe that <a class="el" href="classitpp_1_1Convolutional__Code.html#f3bf2206a471342563a4080e42d6b435" title="Decode a bvec of coded data.">decode()</a> by default also assumes that a tail is added. Both encoding and decoding method can be changed by the <a class="el" href="classitpp_1_1Convolutional__Code.html#1c49283f24dddf4e8cee2835f9d26afe" title="Set encoding and decoding method (Trunc, Tail, or Tailbite).">set_method()</a> function.<p>
377Example of use: (rate 1/3 constraint length K=7 ODS code using <a class="el" href="classitpp_1_1BPSK.html" title="BPSK modulator with real symbols.">BPSK</a> over AWGN) <div class="fragment"><pre class="fragment">  BPSK bpsk;
378  <a class="code" href="classitpp_1_1Convolutional__Code.html#7fa593431fe01986a69247a493d88bae" title="Default constructor - sets (0133,0171) code with tail.">Convolutional_Code</a> code;
379  ivec generator(3);
380  generator(0)=0133;
381  generator(1)=0165;
382  generator(2)=0171;
383  code.set_generator_polynomials(generator, 7);
384
385  bvec bits=<a class="code" href="group__randgen.html#g5aa06887cf1fd3301b040987924068f0" title="Generates a random bit (equally likely 0s and 1s).">randb</a>(100), encoded_bits, decoded_bits;
386  vec tx_signal, rx_signal;
387
388  code.encode_tail(bits, encoded_bits);
389  tx_signal = bpsk.modulate_bits(encoded_bits);
390  rx_signal = tx_signal + <a class="code" href="group__miscfunc.html#gf559d29ca56ad3396a4284964b01a9b0" title="Square root of the elements.">sqrt</a>(0.5)*<a class="code" href="group__randgen.html#g9ecf5af23567f51abc9af737fdbd872a" title="Generates a random Gaussian (0,1) variable.">randn</a>(tx_signal.size());
391  code.decode_tail(rx_signal, decoded_bits);
392</pre></div><p>
393Comment: ODS-code stand for Optimum Distance Spectrum Code. For details see T. Ottosson, "Coding, Modulation and Multiuser Decoding for DS-CDMA Systems," Ph.d. thesis, Department of Information Theory, Scool of Electrical and Computer Engineering, Chalmers University of Technology, Goteborg 1997.<p>
394It is also possible to set the generator polynomials directly using the builtin tables which consists of: Maximum Free Distance (MFD) Codes of rates R=1/2 through R=1/8 and Optimum Distance Spectrum (ODS) Codes of rates R=1/2 through R=1/4. <hr><h2>Member Function Documentation</h2>
395<a class="anchor" name="3f442fd4218c746dc046ea996f301cf7"></a><!-- doxytag: member="itpp::Convolutional_Code::calculate_spectrum" ref="3f442fd4218c746dc046ea996f301cf7" args="(Array&lt; ivec &gt; &amp;spectrum, int dmax, int no_terms)" -->
396<div class="memitem">
397<div class="memproto">
398      <table class="memname">
399        <tr>
400          <td class="memname">void itpp::Convolutional_Code::calculate_spectrum           </td>
401          <td>(</td>
402          <td class="paramtype"><a class="el" href="classitpp_1_1Array.html">Array</a>&lt; ivec &gt; &amp;&nbsp;</td>
403          <td class="paramname"> <em>spectrum</em>, </td>
404        </tr>
405        <tr>
406          <td class="paramkey"></td>
407          <td></td>
408          <td class="paramtype">int&nbsp;</td>
409          <td class="paramname"> <em>dmax</em>, </td>
410        </tr>
411        <tr>
412          <td class="paramkey"></td>
413          <td></td>
414          <td class="paramtype">int&nbsp;</td>
415          <td class="paramname"> <em>no_terms</em></td><td>&nbsp;</td>
416        </tr>
417        <tr>
418          <td></td>
419          <td>)</td>
420          <td></td><td></td><td></td>
421        </tr>
422      </table>
423</div>
424<div class="memdoc">
425
426<p>
427Calculate spectrum.
428<p>
429Calculates both the weight spectrum (Ad) and the information weight spectrum (Cd) and returns it as ivec:s in the 0:th and 1:st component of spectrum, respectively. Suitable for calculating many terms in the spectra (uses an breadth first algorithm). It is assumed that the code is non-catastrophic or else it is a possibility for an eternal loop. dmax = an upper bound on the free distance no_terms = no_terms including the dmax term that should be calculated<p>
430Observe that there is a risk that some of the integers are overflow if many terms are calculated in the spectrum.
431<p>Reimplemented in <a class="el" href="classitpp_1_1Punctured__Convolutional__Code.html#5b03f1aa26a5521cdcab6298d94926c9">itpp::Punctured_Convolutional_Code</a>.</p>
432
433<p>References <a class="el" href="convcode_8h-source.html#l00413">m</a>, <a class="el" href="convcode_8h-source.html#l00372">next_state()</a>, <a class="el" href="convcode_8h-source.html#l00415">no_states</a>, <a class="el" href="array_8h-source.html#l00257">itpp::Array&lt; T &gt;::set_size()</a>, <a class="el" href="sigfun_8cpp-source.html#l00297">itpp::spectrum()</a>, and <a class="el" href="convcode_8cpp-source.html#l00042">weight()</a>.</p>
434
435</div>
436</div><p>
437<a class="anchor" name="9f42d8c8bdb51460ebc7d43deb93bad7"></a><!-- doxytag: member="itpp::Convolutional_Code::decode_tail" ref="9f42d8c8bdb51460ebc7d43deb93bad7" args="(const vec &amp;received_signal, bvec &amp;output)" -->
438<div class="memitem">
439<div class="memproto">
440      <table class="memname">
441        <tr>
442          <td class="memname">void itpp::Convolutional_Code::decode_tail           </td>
443          <td>(</td>
444          <td class="paramtype">const vec &amp;&nbsp;</td>
445          <td class="paramname"> <em>received_signal</em>, </td>
446        </tr>
447        <tr>
448          <td class="paramkey"></td>
449          <td></td>
450          <td class="paramtype">bvec &amp;&nbsp;</td>
451          <td class="paramname"> <em>output</em></td><td>&nbsp;</td>
452        </tr>
453        <tr>
454          <td></td>
455          <td>)</td>
456          <td></td><td></td><td><code> [virtual]</code></td>
457        </tr>
458      </table>
459</div>
460<div class="memdoc">
461
462<p>
463Decode a block of encoded data where encode_tail has been used.
464<p>
465Thus is assumes a decoder start state of zero and that a tail of K-1 zeros has been added. No memory truncation.
466<p>Reimplemented in <a class="el" href="classitpp_1_1Punctured__Convolutional__Code.html#8c706434a618852db7304b6e699c0194">itpp::Punctured_Convolutional_Code</a>.</p>
467
468<p>References <a class="el" href="convcode_8cpp-source.html#l00213">calc_metric()</a>, <a class="el" href="convcode_8h-source.html#l00406">get_input()</a>, <a class="el" href="itassert_8h-source.html#l00117">it_error_if</a>, <a class="el" href="convcode_8h-source.html#l00413">m</a>, <a class="el" href="tcp_8h-source.html#l00117">itpp::max()</a>, <a class="el" href="array_8h-source.html#l00377">itpp::Array&lt; T &gt;::mid()</a>, <a class="el" href="convcode_8h-source.html#l00415">no_states</a>, <a class="el" href="convcode_8h-source.html#l00431">output_reverse_int</a>, <a class="el" href="convcode_8h-source.html#l00435">path_memory</a>, <a class="el" href="convcode_8h-source.html#l00376">previous_state()</a>, <a class="el" href="convcode_8h-source.html#l00439">sum_metric</a>, and <a class="el" href="convcode_8h-source.html#l00437">visited_state</a>.</p>
469
470<p>Referenced by <a class="el" href="convcode_8cpp-source.html#l00747">decode()</a>.</p>
471
472</div>
473</div><p>
474<a class="anchor" name="94f2b7f77dc08fc0fb975735762be742"></a><!-- doxytag: member="itpp::Convolutional_Code::decode_tailbite" ref="94f2b7f77dc08fc0fb975735762be742" args="(const vec &amp;received_signal, bvec &amp;output)" -->
475<div class="memitem">
476<div class="memproto">
477      <table class="memname">
478        <tr>
479          <td class="memname">void itpp::Convolutional_Code::decode_tailbite           </td>
480          <td>(</td>
481          <td class="paramtype">const vec &amp;&nbsp;</td>
482          <td class="paramname"> <em>received_signal</em>, </td>
483        </tr>
484        <tr>
485          <td class="paramkey"></td>
486          <td></td>
487          <td class="paramtype">bvec &amp;&nbsp;</td>
488          <td class="paramname"> <em>output</em></td><td>&nbsp;</td>
489        </tr>
490        <tr>
491          <td></td>
492          <td>)</td>
493          <td></td><td></td><td><code> [virtual]</code></td>
494        </tr>
495      </table>
496</div>
497<div class="memdoc">
498
499<p>
500Decode a block of encoded data where encode_tailbite has been used.
501<p>
502The decoding algorithm tries all start states, so the <a class="el" href="classitpp_1_1Convolutional__Code.html#94f2b7f77dc08fc0fb975735762be742" title="Decode a block of encoded data where encode_tailbite has been used.">decode_tailbite()</a> is <img class="formulaInl" alt="$2^{K-1}$" src="form_242.png"> times more complex than the decode_tail method.
503<p>Reimplemented in <a class="el" href="classitpp_1_1Punctured__Convolutional__Code.html#841c9437974ffa14ff10385e9729f59d">itpp::Punctured_Convolutional_Code</a>.</p>
504
505<p>References <a class="el" href="convcode_8cpp-source.html#l00213">calc_metric()</a>, <a class="el" href="convcode_8h-source.html#l00406">get_input()</a>, <a class="el" href="itassert_8h-source.html#l00117">it_error_if</a>, <a class="el" href="tcp_8h-source.html#l00117">itpp::max()</a>, <a class="el" href="convcode_8h-source.html#l00415">no_states</a>, <a class="el" href="convcode_8h-source.html#l00431">output_reverse_int</a>, <a class="el" href="convcode_8h-source.html#l00435">path_memory</a>, <a class="el" href="convcode_8h-source.html#l00376">previous_state()</a>, <a class="el" href="convcode_8h-source.html#l00439">sum_metric</a>, and <a class="el" href="convcode_8h-source.html#l00437">visited_state</a>.</p>
506
507<p>Referenced by <a class="el" href="convcode_8cpp-source.html#l00747">decode()</a>.</p>
508
509</div>
510</div><p>
511<a class="anchor" name="a6884e3f60678177fbf60e22d2447a5b"></a><!-- doxytag: member="itpp::Convolutional_Code::encode_bit" ref="a6884e3f60678177fbf60e22d2447a5b" args="(const bin &amp;input, bvec &amp;output)" -->
512<div class="memitem">
513<div class="memproto">
514      <table class="memname">
515        <tr>
516          <td class="memname">void itpp::Convolutional_Code::encode_bit           </td>
517          <td>(</td>
518          <td class="paramtype">const <a class="el" href="classitpp_1_1bin.html">bin</a> &amp;&nbsp;</td>
519          <td class="paramname"> <em>input</em>, </td>
520        </tr>
521        <tr>
522          <td class="paramkey"></td>
523          <td></td>
524          <td class="paramtype">bvec &amp;&nbsp;</td>
525          <td class="paramname"> <em>output</em></td><td>&nbsp;</td>
526        </tr>
527        <tr>
528          <td></td>
529          <td>)</td>
530          <td></td><td></td><td></td>
531        </tr>
532      </table>
533</div>
534<div class="memdoc">
535
536<p>
537Encode a binary bit starting from the internal encoder state.
538<p>
539To initialize the encoder state use <a class="el" href="classitpp_1_1Convolutional__Code.html#6316d7d75c01471aa44d533fdaa586c1" title="Set encoder default start state.">set_start_state()</a> and <a class="el" href="classitpp_1_1Convolutional__Code.html#9ef6fc1934531d3c12123ed90c5b4c40" title="Initialise internal encoder state with start state. Has no effect on Tail and Tailbite...">init_encoder()</a> 
540<p>References <a class="el" href="convcode_8h-source.html#l00421">encoder_state</a>, <a class="el" href="convcode_8h-source.html#l00417">gen_pol</a>, <a class="el" href="convcode_8h-source.html#l00413">m</a>, and <a class="el" href="convcode_8h-source.html#l00429">xor_int_table</a>.</p>
541
542</div>
543</div><p>
544<a class="anchor" name="47230acfea5aa32cb31e63abca1d222e"></a><!-- doxytag: member="itpp::Convolutional_Code::encode_tail" ref="47230acfea5aa32cb31e63abca1d222e" args="(const bvec &amp;input, bvec &amp;output)" -->
545<div class="memitem">
546<div class="memproto">
547      <table class="memname">
548        <tr>
549          <td class="memname">void itpp::Convolutional_Code::encode_tail           </td>
550          <td>(</td>
551          <td class="paramtype">const bvec &amp;&nbsp;</td>
552          <td class="paramname"> <em>input</em>, </td>
553        </tr>
554        <tr>
555          <td class="paramkey"></td>
556          <td></td>
557          <td class="paramtype">bvec &amp;&nbsp;</td>
558          <td class="paramname"> <em>output</em></td><td>&nbsp;</td>
559        </tr>
560        <tr>
561          <td></td>
562          <td>)</td>
563          <td></td><td></td><td></td>
564        </tr>
565      </table>
566</div>
567<div class="memdoc">
568
569<p>
570Encoding that starts and ends in the zero state.
571<p>
572Encode a binary vector of inputs starting from zero state and also adds a tail of K-1 zeros to force the encoder into the zero state. Well suited for packet transmission.<p>
573<dl class="note" compact><dt><b>Note:</b></dt><dd>The <a class="el" href="classitpp_1_1Convolutional__Code.html#9ef6fc1934531d3c12123ed90c5b4c40" title="Initialise internal encoder state with start state. Has no effect on Tail and Tailbite...">init_encoder()</a> function has no effect on the starting state for this method. </dd></dl>
574
575<p>Reimplemented in <a class="el" href="classitpp_1_1Punctured__Convolutional__Code.html#eda7709de1cff7c6211884f9acfae470">itpp::Punctured_Convolutional_Code</a>.</p>
576
577<p>References <a class="el" href="convcode_8h-source.html#l00421">encoder_state</a>, <a class="el" href="convcode_8h-source.html#l00417">gen_pol</a>, <a class="el" href="convcode_8h-source.html#l00413">m</a>, and <a class="el" href="convcode_8h-source.html#l00429">xor_int_table</a>.</p>
578
579<p>Referenced by <a class="el" href="convcode_8cpp-source.html#l00619">encode()</a>.</p>
580
581</div>
582</div><p>
583<a class="anchor" name="34e2691d01bc0b35d81f109f27bedfa2"></a><!-- doxytag: member="itpp::Convolutional_Code::encode_tailbite" ref="34e2691d01bc0b35d81f109f27bedfa2" args="(const bvec &amp;input, bvec &amp;output)" -->
584<div class="memitem">
585<div class="memproto">
586      <table class="memname">
587        <tr>
588          <td class="memname">void itpp::Convolutional_Code::encode_tailbite           </td>
589          <td>(</td>
590          <td class="paramtype">const bvec &amp;&nbsp;</td>
591          <td class="paramname"> <em>input</em>, </td>
592        </tr>
593        <tr>
594          <td class="paramkey"></td>
595          <td></td>
596          <td class="paramtype">bvec &amp;&nbsp;</td>
597          <td class="paramname"> <em>output</em></td><td>&nbsp;</td>
598        </tr>
599        <tr>
600          <td></td>
601          <td>)</td>
602          <td></td><td></td><td></td>
603        </tr>
604      </table>
605</div>
606<div class="memdoc">
607
608<p>
609Encode an input binary vector using tailbiting.
610<p>
611In the Tailbiting method the starting state of the encoder is initialised with the last K-1 bits of the input vector. This gives an additional information to the decoder that the starting and ending states are identical, although not known a priori.<p>
612Well suited for packet transmission with small packets, because there is no tail overhead as in the Tail method.<p>
613<dl class="note" compact><dt><b>Note:</b></dt><dd>The <a class="el" href="classitpp_1_1Convolutional__Code.html#9ef6fc1934531d3c12123ed90c5b4c40" title="Initialise internal encoder state with start state. Has no effect on Tail and Tailbite...">init_encoder()</a> function has no effect on the starting state for this method. </dd></dl>
614
615<p>Reimplemented in <a class="el" href="classitpp_1_1Punctured__Convolutional__Code.html#60feaefdc4f8b62884268f7cc0ea8296">itpp::Punctured_Convolutional_Code</a>.</p>
616
617<p>References <a class="el" href="convcode_8h-source.html#l00421">encoder_state</a>, <a class="el" href="convcode_8h-source.html#l00417">gen_pol</a>, <a class="el" href="convcode_8h-source.html#l00413">m</a>, and <a class="el" href="convcode_8h-source.html#l00429">xor_int_table</a>.</p>
618
619<p>Referenced by <a class="el" href="convcode_8cpp-source.html#l00619">encode()</a>.</p>
620
621</div>
622</div><p>
623<a class="anchor" name="b2acc3b632782ff035fa1b5b2b122153"></a><!-- doxytag: member="itpp::Convolutional_Code::encode_trunc" ref="b2acc3b632782ff035fa1b5b2b122153" args="(const bvec &amp;input, bvec &amp;output)" -->
624<div class="memitem">
625<div class="memproto">
626      <table class="memname">
627        <tr>
628          <td class="memname">void itpp::Convolutional_Code::encode_trunc           </td>
629          <td>(</td>
630          <td class="paramtype">const bvec &amp;&nbsp;</td>
631          <td class="paramname"> <em>input</em>, </td>
632        </tr>
633        <tr>
634          <td class="paramkey"></td>
635          <td></td>
636          <td class="paramtype">bvec &amp;&nbsp;</td>
637          <td class="paramname"> <em>output</em></td><td>&nbsp;</td>
638        </tr>
639        <tr>
640          <td></td>
641          <td>)</td>
642          <td></td><td></td><td></td>
643        </tr>
644      </table>
645</div>
646<div class="memdoc">
647
648<p>
649Encode a binary vector starting from the previous encoder state.
650<p>
651The initial encoder state can be changed using <a class="el" href="classitpp_1_1Convolutional__Code.html#6316d7d75c01471aa44d533fdaa586c1" title="Set encoder default start state.">set_start_state()</a> and <a class="el" href="classitpp_1_1Convolutional__Code.html#9ef6fc1934531d3c12123ed90c5b4c40" title="Initialise internal encoder state with start state. Has no effect on Tail and Tailbite...">init_encoder()</a> functions.
652<p>Reimplemented in <a class="el" href="classitpp_1_1Punctured__Convolutional__Code.html#49dbb58e8a99c89502140e8f2d527503">itpp::Punctured_Convolutional_Code</a>.</p>
653
654<p>References <a class="el" href="convcode_8h-source.html#l00421">encoder_state</a>, <a class="el" href="convcode_8h-source.html#l00417">gen_pol</a>, <a class="el" href="convcode_8h-source.html#l00413">m</a>, and <a class="el" href="convcode_8h-source.html#l00429">xor_int_table</a>.</p>
655
656<p>Referenced by <a class="el" href="convcode_8cpp-source.html#l00619">encode()</a>.</p>
657
658</div>
659</div><p>
660<a class="anchor" name="8217a8922992b1fb4faa28d86f21e6d7"></a><!-- doxytag: member="itpp::Convolutional_Code::fast" ref="8217a8922992b1fb4faa28d86f21e6d7" args="(Array&lt; ivec &gt; &amp;spectrum, const int dfree, const int no_terms, const int Cdfree=1000000, const bool test_catastrophic=false)" -->
661<div class="memitem">
662<div class="memproto">
663      <table class="memname">
664        <tr>
665          <td class="memname">int itpp::Convolutional_Code::fast           </td>
666          <td>(</td>
667          <td class="paramtype"><a class="el" href="classitpp_1_1Array.html">Array</a>&lt; ivec &gt; &amp;&nbsp;</td>
668          <td class="paramname"> <em>spectrum</em>, </td>
669        </tr>
670        <tr>
671          <td class="paramkey"></td>
672          <td></td>
673          <td class="paramtype">const int&nbsp;</td>
674          <td class="paramname"> <em>dfree</em>, </td>
675        </tr>
676        <tr>
677          <td class="paramkey"></td>
678          <td></td>
679          <td class="paramtype">const int&nbsp;</td>
680          <td class="paramname"> <em>no_terms</em>, </td>
681        </tr>
682        <tr>
683          <td class="paramkey"></td>
684          <td></td>
685          <td class="paramtype">const int&nbsp;</td>
686          <td class="paramname"> <em>Cdfree</em> = <code>1000000</code>, </td>
687        </tr>
688        <tr>
689          <td class="paramkey"></td>
690          <td></td>
691          <td class="paramtype">const bool&nbsp;</td>
692          <td class="paramname"> <em>test_catastrophic</em> = <code>false</code></td><td>&nbsp;</td>
693        </tr>
694        <tr>
695          <td></td>
696          <td>)</td>
697          <td></td><td></td><td></td>
698        </tr>
699      </table>
700</div>
701<div class="memdoc">
702
703<p>
704Cederwall's fast algorithm.
705<p>
706Calculates both the weight spectrum (Ad) and the information weight spectrum (Cd) and returns it as ivec:s in the 0:th and 1:st component of spectrum, respectively. The FAST algorithm is good for calculating only a few terms in the spectrum. If many terms are desired, use calc_spectrum instead. The algorithm returns -1 if the code tested is worse that the input dfree and Cdfree. It returns 0 if the code MAY be catastrophic (assuming that test_catastrophic is true), and returns 1 if everything went right.<p>
707<ul>
708<li><code>dfree</code> the free distance of the code (or an upper bound) </li>
709<li><code>no_terms</code> including the dfree term that should be calculated </li>
710<li><code>Cdfree</code> is the best value of information weight spectrum found so far</li>
711</ul>
712Observe that there is a risk that some of the integers are overflow if many terms are calculated in the spectrum.<p>
713See IT No. 6, pp. 1146-1159, Nov. 1989 for details.
714<p>References <a class="el" href="convcode_8cpp-source.html#l01130">distance_profile()</a>, <a class="el" href="convcode_8h-source.html#l00413">m</a>, <a class="el" href="convcode_8h-source.html#l00372">next_state()</a>, <a class="el" href="matfunc_8h-source.html#l00777">itpp::reverse()</a>, <a class="el" href="array_8h-source.html#l00257">itpp::Array&lt; T &gt;::set_size()</a>, <a class="el" href="sigfun_8cpp-source.html#l00297">itpp::spectrum()</a>, <a class="el" href="convcode_8cpp-source.html#l00042">weight()</a>, and <a class="el" href="convcode_8cpp-source.html#l00064">weight_reverse()</a>.</p>
715
716</div>
717</div><p>
718<a class="anchor" name="635406cac085c188709234c688ce2c68"></a><!-- doxytag: member="itpp::Convolutional_Code::inverse_tail" ref="635406cac085c188709234c688ce2c68" args="(const bvec coded_sequence, bvec &amp;input)" -->
719<div class="memitem">
720<div class="memproto">
721      <table class="memname">
722        <tr>
723          <td class="memname">bool itpp::Convolutional_Code::inverse_tail           </td>
724          <td>(</td>
725          <td class="paramtype">const bvec&nbsp;</td>
726          <td class="paramname"> <em>coded_sequence</em>, </td>
727        </tr>
728        <tr>
729          <td class="paramkey"></td>
730          <td></td>
731          <td class="paramtype">bvec &amp;&nbsp;</td>
732          <td class="paramname"> <em>input</em></td><td>&nbsp;</td>
733        </tr>
734        <tr>
735          <td></td>
736          <td>)</td>
737          <td></td><td></td><td></td>
738        </tr>
739      </table>
740</div>
741<div class="memdoc">
742
743<p>
744Calculate the inverse sequence.
745<p>
746Assumes that encode_tail is used in the encoding process. Returns false if there is an error in the coded sequence (not a valid codeword). Do not check that the tail forces the encoder into the zeroth state.
747<p>Reimplemented in <a class="el" href="classitpp_1_1Punctured__Convolutional__Code.html#b9fa55cd0b92e4d0db5debcd198184b1">itpp::Punctured_Convolutional_Code</a>.</p>
748
749<p>References <a class="el" href="convcode_8h-source.html#l00417">gen_pol</a>, <a class="el" href="itassert_8h-source.html#l00117">it_error_if</a>, <a class="el" href="convcode_8h-source.html#l00413">m</a>, and <a class="el" href="convcode_8h-source.html#l00429">xor_int_table</a>.</p>
750
751</div>
752</div><p>
753<a class="anchor" name="9860c6e22e6f7a58c020534045a432d0"></a><!-- doxytag: member="itpp::Convolutional_Code::set_code" ref="9860c6e22e6f7a58c020534045a432d0" args="(const CONVOLUTIONAL_CODE_TYPE type_of_code, int inverse_rate, int constraint_length)" -->
754<div class="memitem">
755<div class="memproto">
756      <table class="memname">
757        <tr>
758          <td class="memname">void itpp::Convolutional_Code::set_code           </td>
759          <td>(</td>
760          <td class="paramtype">const <a class="el" href="group__fec.html#ge9651aa649deec69310af24cd89b8729">CONVOLUTIONAL_CODE_TYPE</a>&nbsp;</td>
761          <td class="paramname"> <em>type_of_code</em>, </td>
762        </tr>
763        <tr>
764          <td class="paramkey"></td>
765          <td></td>
766          <td class="paramtype">int&nbsp;</td>
767          <td class="paramname"> <em>inverse_rate</em>, </td>
768        </tr>
769        <tr>
770          <td class="paramkey"></td>
771          <td></td>
772          <td class="paramtype">int&nbsp;</td>
773          <td class="paramname"> <em>constraint_length</em></td><td>&nbsp;</td>
774        </tr>
775        <tr>
776          <td></td>
777          <td>)</td>
778          <td></td><td></td><td></td>
779        </tr>
780      </table>
781</div>
782<div class="memdoc">
783
784<p>
785Set the code according to built-in tables.
786<p>
787The <em>type_of_code</em> can be either <em>MFD</em> or <em>ODS</em> for maximum free distance codes (according to Proakis) or Optimum Distance Spectrum Codes according to Frenger, Orten and Ottosson.
788<p>Reimplemented in <a class="el" href="classitpp_1_1Punctured__Convolutional__Code.html#3b8b66d056a2cde7ad92a8b6ce0c19ba">itpp::Punctured_Convolutional_Code</a>.</p>
789
790<p>References <a class="el" href="itassert_8h-source.html#l00094">it_assert</a>, and <a class="el" href="convcode_8cpp-source.html#l00552">set_generator_polynomials()</a>.</p>
791
792<p>Referenced by <a class="el" href="convcode_8h-source.html#l00106">Convolutional_Code()</a>.</p>
793
794</div>
795</div><p>
796<hr><h2>Friends And Related Function Documentation</h2>
797<a class="anchor" name="4abebe627013b4dfb5e1025c1f94c769"></a><!-- doxytag: member="itpp::Convolutional_Code::compare_spectra" ref="4abebe627013b4dfb5e1025c1f94c769" args="(ivec v1, ivec v2, vec weight_profile)" -->
798<div class="memitem">
799<div class="memproto">
800      <table class="memname">
801        <tr>
802          <td class="memname">int compare_spectra           </td>
803          <td>(</td>
804          <td class="paramtype">ivec&nbsp;</td>
805          <td class="paramname"> <em>v1</em>, </td>
806        </tr>
807        <tr>
808          <td class="paramkey"></td>
809          <td></td>
810          <td class="paramtype">ivec&nbsp;</td>
811          <td class="paramname"> <em>v2</em>, </td>
812        </tr>
813        <tr>
814          <td class="paramkey"></td>
815          <td></td>
816          <td class="paramtype">vec&nbsp;</td>
817          <td class="paramname"> <em>weight_profile</em></td><td>&nbsp;</td>
818        </tr>
819        <tr>
820          <td></td>
821          <td>)</td>
822          <td></td><td></td><td><code> [related]</code></td>
823        </tr>
824      </table>
825</div>
826<div class="memdoc">
827
828<p>
829Compare two distance spectra using a weight profile.
830<p>
831Return 1 if v1 is less, 0 if v2 less, and -1 if equal.
832</div>
833</div><p>
834<hr>The documentation for this class was generated from the following files:<ul>
835<li><a class="el" href="convcode_8h-source.html">convcode.h</a><li><a class="el" href="convcode_8cpp.html">convcode.cpp</a></ul>
836</div>
837<hr size="1"><address style="text-align: right;"><small>Generated on Tue Jun 2 10:02:19 2009 for mixpp by&nbsp;
838<a href="http://www.doxygen.org/index.html">
839<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address>
840</body>
841</html>
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