pf
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A class template for HMM filtering. More...
#include <cf_filters.h>
Public Types | |
using | ssv = Eigen::Matrix< float_t, dimstate, 1 > |
"state size vector" | |
using | osv = Eigen::Matrix< float_t, dimobs, 1 > |
"observation size vector" | |
using | ssMat = Eigen::Matrix< float_t, dimstate, dimstate > |
"state size matrix" | |
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using | ssv = Eigen::Matrix< float_t, dimstate, 1 > |
using | osv = Eigen::Matrix< float_t, dimstate, 1 > |
Public Member Functions | |
hmm () | |
Default constructor. More... | |
hmm (const ssv &initStateDistr, const ssMat &transMat) | |
Constructor. More... | |
virtual | ~hmm () |
The (virtual) desuctor. | |
float_t | getLogCondLike () const |
Get the latest conditional likelihood. More... | |
ssv | getFilterVec () const |
Get the current filter vector. More... | |
void | update (const ssv &condDensVec) |
Perform a HMM filter update. More... | |
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virtual | ~cf_filter () |
The (virtual) destructor. | |
Private Attributes | |
ssv | m_filtVec |
filter vector | |
ssMat | m_transMatTranspose |
transition matrix | |
float_t | m_lastCondLike |
last conditional likelihood | |
bool | m_fresh |
has data been observed? | |
A class template for HMM filtering.
hmm< dimstate, dimobs, float_t >::hmm | ( | ) |
Default constructor.
Need ths fir constructing default std::array<>s. Fills all vectors and matrices with zeros.
hmm< dimstate, dimobs, float_t >::hmm | ( | const ssv & | initStateDistr, |
const ssMat & | transMat | ||
) |
Constructor.
allows specification of initstate distn and transition matrix.
initStateDistr | first time state prior distribution. |
transMat | time homogeneous transition matrix. |
auto hmm< dimstate, dimobs, float_t >::getFilterVec | ( | ) | const |
Get the current filter vector.
get the current filter vector.
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virtual |
Get the latest conditional likelihood.
Implements cf_filter< dimstate, dimobs, float_t >.
void hmm< dimstate, dimobs, float_t >::update | ( | const ssv & | condDensVec | ) |
Perform a HMM filter update.
Perform a HMM filter update.
condDensVec | the vector (in x_t) of p(y_t|x_t) |