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Timestamp:
03/06/09 15:03:45 (15 years ago)
Author:
smidl
Message:

correction of ARX tutorial

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1 modified

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  • doc/tutorial/tut_arx.dox

    r272 r290  
    3030For online estimation with stationary parameters can be easily achieved by collecting the sufficient statistics described above recursively. 
    3131 
    32 Extension to non-stationaly parameters, \f$ \theta_t , r_t \f$ can be achieved by operation called forgetting. This is an approximation of Bayesian filtering see [Kulhavy]. The resulting algorithm is defined by manipulation of sfficient statistics: 
     32Extension to non-stationaly parameters, \f$ \theta_t , r_t \f$ can be achieved by operation called forgetting. This is an approximation of Bayesian filtering see [Kulhavy]. The resulting algorithm is defined by manipulation of sufficient statistics: 
    3333<dl> 
    3434<dt>Information matrix</dt> <dd>which is a sum of outer products \f[  
    35 V_t = V_{t-1} + \phi \left[\begin{array}{c}y_{t}\\ \psi_{t}\end{array}\right] 
     35V_t = \phi V_{t-1} + \left[\begin{array}{c}y_{t}\\ \psi_{t}\end{array}\right] 
    3636\begin{array}{c} [y_{t}',\,\psi_{t}']\\ \\\end{array} 
    3737+(1-\phi) V_0 
    3838\f]</dd> 
    3939<dt>"Degree of freedom"</dd>  <dd>which is an accumulator of number of data records \f[ 
    40 \nu_t = \nu_{t-1} + \phi + (1-\phi) \nu_0 
     40\nu_t = \phi \nu_{t-1} + 1 + (1-\phi) \nu_0 
    4141\f]</dd> 
    4242</dl>