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113 lines (106 loc) · 3 KB
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#include "fcl_util.h"
#include "logger/network_logger.h"
#include <math.h>
/**
* GNU GENERAL PUBLIC LICENSE
* Version 3, 29 June 2007
*
* (C) 2017, Bernd Porr <bernd@glasgowneuro.tech>
* (C) 2017, Paul Miller <paul@glasgowneuro.tech>
**/
FeedforwardClosedloopLearningWithFilterbank::FeedforwardClosedloopLearningWithFilterbank(
const int num_of_inputs,
const std::vector<int> &num_of_neurons_per_layer,
const int num_filtersInput,
const double minT,
const double maxT) : FeedforwardClosedloopLearning(
num_of_inputs * num_filtersInput,
num_of_neurons_per_layer) {
#ifdef DEBUG
fprintf(stderr,"Creating instance of FeedforwardClosedloopLearningWithFilterbank.\n");
#endif
nFiltersPerInput = num_filtersInput;
nInputs = num_of_inputs;
assert((nInputs*nFiltersPerInput) == getNumInputs());
bandpass = new FCLBandpass**[num_of_inputs];
errors.resize(num_of_inputs*num_filtersInput);
filterbankOutputs.resize(num_of_inputs * num_filtersInput);
#ifdef DEBUG
networkLogger = new NetworkLogger(this);
networkLogger->log();
#endif
for(int i=0;i<num_of_inputs;i++) {
bandpass[i] = new FCLBandpass*[num_filtersInput];
double fs = 1;
double fmin = fs/maxT;
double fmax = fs/minT;
double df = (fmax-fmin)/((double)(num_filtersInput-1));
double f = fmin;
#ifdef DEBUG
fprintf(stderr,"bandpass: fmin=%f,fmax=%f,df=%f\n",fmin,fmax,df);
#endif
for(int j=0;j<num_filtersInput;j++) {
bandpass[i][j] = new FCLBandpass();
#ifdef DEBUG
fprintf(stderr,"bandpass[%d][%d]->setParameters(%f,%f)\n",
i,j,f,dampingCoeff);
#endif
bandpass[i][j]->setParameters(f,dampingCoeff);
f = f + df;
#ifdef DEBUG
for(int k=0;k<maxT;k++) {
double a = 0;
if (k==minT) {
a = 1;
}
double b = bandpass[i][j]->filter(a);
assert(b != NAN);
assert(b != INFINITY);
}
#endif
bandpass[i][j]->reset();
errors[i*nFiltersPerInput+j] = 0;
}
}
}
FeedforwardClosedloopLearningWithFilterbank::~FeedforwardClosedloopLearningWithFilterbank() {
for(int i=0;i<nInputs;i++) {
for(int j=0;j<nFiltersPerInput;j++) {
delete bandpass[i][j];
}
delete[] bandpass[i];
}
delete[] bandpass;
}
void FeedforwardClosedloopLearningWithFilterbank::doStep(const std::vector<double> &input,
const std::vector<double> &error) {
if (input.size() != (unsigned)nInputs) {
char tmp[256];
sprintf(tmp,"Input array dim mismatch: got: %ld, want: %d.",input.size(),nInputs);
#ifdef DEBUG
fprintf(stderr,"%s\n",tmp);
#endif
throw tmp;
}
if (error.size() != (unsigned)nInputs) {
char tmp[256];
sprintf(tmp,
"Error array dim mismatch: got: %ld, want: %d "
"which is the number of inputs.",
error.size(),nInputs);
#ifdef DEBUG
fprintf(stderr,"%s\n",tmp);
#endif
throw tmp;
}
#ifdef DEBUG
networkLogger->logLayers();
#endif
for(int i=0;i<nInputs;i++) {
for(int j=0;j<nFiltersPerInput;j++) {
filterbankOutputs[i*nFiltersPerInput+j] = bandpass[i][j]->filter(input[i]);
errors[i*nFiltersPerInput+j] = error[i];
}
}
FeedforwardClosedloopLearning::doStep(filterbankOutputs, errors);
}