root/doc/latex/annotated.tex @ 22

Revision 22, 2.8 kB (checked in by smidl, 17 years ago)

upravy Kalmana

  • Property svn:eol-style set to native
Line 
1\section{mixpp Class List}
2Here are the classes, structs, unions and interfaces with brief descriptions:\begin{CompactList}
3\item\contentsline{section}{{\bf bilinfn} (Class representing function \$f(x,u) = Ax+Bu\$ )}{\pageref{classbilinfn}}{}
4\item\contentsline{section}{{\bf BM} (Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities )}{\pageref{classBM}}{}
5\item\contentsline{section}{{\bf constfn} (Class representing function \$f(x) = a\$, here rv is empty )}{\pageref{classconstfn}}{}
6\item\contentsline{section}{{\bf diffbifn} (Class representing a differentiable function of two variables \$f(x,u)\$ )}{\pageref{classdiffbifn}}{}
7\item\contentsline{section}{{\bf DS} (Abstract class for discrete-time sources of data )}{\pageref{classDS}}{}
8\item\contentsline{section}{{\bf eEF} (General conjugate exponential family posterior density )}{\pageref{classeEF}}{}
9\item\contentsline{section}{{\bf EKF$<$ sq\_\-T $>$} (Extended \doxyref{Kalman}{p.}{classKalman} Filter )}{\pageref{classEKF}}{}
10\item\contentsline{section}{{\bf enorm$<$ sq\_\-T $>$} (Gaussian density with positive definite (decomposed) covariance matrix )}{\pageref{classenorm}}{}
11\item\contentsline{section}{{\bf epdf} (Probability density function with numerical statistics, e.g. posterior density )}{\pageref{classepdf}}{}
12\item\contentsline{section}{{\bf fnc} (Class representing function \$f(x)\$ of variable \$x\$ represented by {\tt rv} )}{\pageref{classfnc}}{}
13\item\contentsline{section}{{\bf fsqmat} (Fake \doxyref{sqmat}{p.}{classsqmat}. This class maps \doxyref{sqmat}{p.}{classsqmat} operations to operations on full matrix )}{\pageref{classfsqmat}}{}
14\item\contentsline{section}{{\bf Kalman$<$ sq\_\-T $>$} (\doxyref{Kalman}{p.}{classKalman} filter with covariance matrices in square root form )}{\pageref{classKalman}}{}
15\item\contentsline{section}{{\bf KalmanFull} (Basic \doxyref{Kalman}{p.}{classKalman} filter with full matrices (education purpose only)! Will be deleted soon! )}{\pageref{classKalmanFull}}{}
16\item\contentsline{section}{{\bf linfn} (Class representing function \$f(x) = Ax+B\$ )}{\pageref{classlinfn}}{}
17\item\contentsline{section}{{\bf MemDS} (Class representing off-line data stored in memory )}{\pageref{classMemDS}}{}
18\item\contentsline{section}{{\bf mpdf} (Conditional probability density, e.g. modeling some dependencies )}{\pageref{classmpdf}}{}
19\item\contentsline{section}{{\bf PF} (A Particle Filter prototype )}{\pageref{classPF}}{}
20\item\contentsline{section}{{\bf RV} (Class representing variables, most often random variables )}{\pageref{classRV}}{}
21\item\contentsline{section}{{\bf sqmat} (Virtual class for representation of double symmetric matrices in square-root form )}{\pageref{classsqmat}}{}
22\item\contentsline{section}{{\bf TrivialPF} (Trivial particle filter with proposal density that is not conditioned on the data )}{\pageref{classTrivialPF}}{}
23\end{CompactList}
Note: See TracBrowser for help on using the browser.