#include <ParaSearch.hh>
Public Methods | |
ParaSearch () | |
virtual | ~ParaSearch () |
void | Allocate (int nb_parameters, int nbLevel, int nb_MTClasses, int nb_SubGMTClasses, int min_Sample, int max_Sample, int nb_TimeSamples) |
memory allocation method. | |
void | Init (SearchTree ****searchTreeCollec, float ****costss, vector< int > *kMTa, vector< int > *kMTb, vector< int > *firstSample) |
Initialisation of the different pointers : to the tree structures, the costs collection and the a posteriori collection of sub-graphs. | |
void | Init (vector< int > *kMTa, vector< int > *kMTb, vector< int > *firstSample) |
Initialisation of the pointers the a posteriori collection of sub-graphs. | |
void | MaxCostalues () |
Calculation method of the maximum values of the matching costs. | |
void | MMSEestim (int interestkMTa, int interestkMTb, int interestfirstSample) |
Method to perform a MMSE estimate of the parameter vector of the similarity model. | |
float | ReevaluateMatch (int i, int j, int k) |
Method to update of the similarity with a new parameter vector. More... | |
void | ErasePdf () |
Method use to transfom into a flat distribution the learned multinomial distributions. | |
Public Attributes | |
int | nbPara |
number of elements in the parameter vector of the similarity model. | |
int | nbQuantifLevel |
number of bins used for the interactive estimation of the multinomial distributions. | |
int | nbMTClasses |
number of MT classes composing the global graph. | |
int | nbSubGMTClasses |
number of MT classes considered per sub-graph in the matching procedure. | |
int | minSample |
Minimum time sample considered in the global graph. | |
int | maxSample |
Maximum time sample considered in the global graph. | |
int | nbTimeSamples |
number of samples of the time-window. | |
SearchTree **** | treeCollec |
pointer to collections of SearchTree objects. | |
float **** | costs |
pointer to collections of distorsion costs array. More... | |
vector< int > | kMTaSorted |
vector of MT class indexes attached to the elements of the a posteriori collection of sub-graphs. | |
vector< int > | kMTbSorted |
vector of 2nd MT class indexes attached to the elements of the a posteriori collection of sub-graphs (only when 2 MT classes are considered simultaneously per sub-graph). | |
vector< int > | firstSampleSorted |
array of first time sample indexes attached to the elements of the a posteriori collection of sub-graphs. | |
float ** | |
array of multinomial distributions for approximating the paramter vector of the similarity model PDF. | |
float * | maxPdf |
array of maximum values of the multinomial distributions. | |
float * | meanPdf |
array of mean values of the multinomial distributions. | |
float * | estimPara |
array of MMSE parameter estimates of the similarity model. | |
float * | estimParaPrevious |
array of MMSE parameter estimates of the similarity model at the previous learning iteration. | |
float * | maxCostValue |
array of maximum cost values. |
For this, the Multinomial distributions, which are the parameter distributions learned by the system, are used to evaluate with MMSE estimator the currently learned parameter vector of the similarity model.
Definition at line 32 of file ParaSearch.hh.
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Method to update of the similarity with a new parameter vector. This methods calls the SearchTree object method 'LowestCosts(...)'which updats the matching costs with a new parameter vector while using the already created tree structure. It returns the updated costs related to the contribution of the different graph's attribute for the updated best mapping function (path of minimal cost) Definition at line 187 of file ParaSearch.hh. |
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pointer to collections of distorsion costs array. The cost assigned during the matchingprocedure to the best mapping function is decomposed into several parts related to each attribute contribution. These different cost constribution are stored in the array 'costs'. Definition at line 57 of file ParaSearch.hh. |