LinearConstraint::LinearConstraint(const Matrix& A, const ColumnVector& b,
const bool rowFlag):
numOfCons_( A.Nrows() ), numOfVars_( A.Ncols() ), nnzl_(0), nnzu_(0),
A_(A), Ax_( A.Nrows() ), lower_( A.Nrows() ), upper_( A.Nrows() ),
cvalue_( A.Nrows()), cviolation_( A.Nrows() ),
constraintMappingIndices_(0), stdForm_(rowFlag)
{
int i;
cvalue_ = 1.0e30; cviolation_ = 0.0;
if( stdForm_ ){
lower_ = b;
upper_ = MAX_BND;
for(i = 1; i <= numOfCons_; i++){
if (lower_(i) > -BIG_BND){
constraintMappingIndices_.append(i);
nnzl_++;
}
}
}
else{
upper_ = b;
lower_ = MIN_BND;
for(i = 1; i <= numOfCons_; i++){
if (upper_(i) < BIG_BND){
constraintMappingIndices_.append(i);
nnzu_++;
}
}
}
numOfCons_ = nnzl_ + nnzu_;
}
LinearConstraint::LinearConstraint(const Matrix& A, const ColumnVector& b):
numOfCons_( A.Nrows() ), numOfVars_( A.Ncols() ), nnzl_(0), nnzu_(0),
A_(A), Ax_( A.Nrows() ), lower_( b ), upper_( b ),
cvalue_( A.Nrows() ), cviolation_( A.Nrows() ),
constraintMappingIndices_(0), stdForm_(true)
{
cvalue_ = 1.0e30; cviolation_ = 0.0;
for(int i = 1; i <= numOfCons_; i++){
if(lower_(i) > -BIG_BND ){
constraintMappingIndices_.append(i);
nnzl_++;
}
}
numOfCons_ = nnzl_;
}
void
MFCC::init()
{
unsigned int i,j;
unsigned int chan;
if (inSize_ != DEFAULT_WIN_SIZE)
{
cerr << "MFCC::init warning inSize_ != 512\n" << endl ;
}
// Initialize frequency boundaries for the filters
freqs_.create(42);
lowestFrequency_ = 133.3333f;
linearFilters_ = 13;
linearSpacing_ = 66.66666f;
logFilters_ = 27;
logSpacing_ = 1.0711703f;
totalFilters_ = linearFilters_ + logFilters_;
lower_.create(totalFilters_);
center_.create(totalFilters_);
upper_.create(totalFilters_);
triangle_heights_.create(totalFilters_);
// Linear filter boundaries
for (i=0; i< linearFilters_; i++)
freqs_(i) = lowestFrequency_ + i * linearSpacing_;
// Logarithmic filter boundaries
float first_log = freqs_(linearFilters_-1);
for (i=1; i<=logFilters_+2; i++)
{
freqs_(linearFilters_-1+i) = first_log * pow(logSpacing_, (float)i);
}
// Triangles information
for (i=0; i<totalFilters_; i++)
lower_(i) = freqs_(i);
for (i=1; i<= totalFilters_; i++)
center_(i-1) = freqs_(i);
for (i=2; i<= totalFilters_+1; i++)
upper_(i-2) = freqs_(i);
for (i=0; i<totalFilters_; i++)
triangle_heights_(i) = 2.0 / (upper_(i) - lower_(i));
fftSize_ = 512;
samplingRate_ = 22050;
fftFreqs_.create(fftSize_);
cepstralCoefs_ = 13;
for (i=0; i< fftSize_; i++)
fftFreqs_(i) = (float)i / (float)fftSize_ * (float)samplingRate_;
mfccFilterWeights_.create(totalFilters_, fftSize_);
mfccDCT_.create(cepstralCoefs_, totalFilters_);
// Initialize mfccFilterWeights
for (chan = 0; chan < totalFilters_; chan++)
for (i=0; i< fftSize_; i++)
{
if ((fftFreqs_(i) > lower_(chan))&& (fftFreqs_(i) <= center_(chan)))
{
mfccFilterWeights_(chan, i) = triangle_heights_(chan) *
((fftFreqs_(i) - lower_(chan))/(center_(chan) - lower_(chan)));
}
if ((fftFreqs_(i) > center_(chan)) && (fftFreqs_(i) <= upper_(chan)))
{
mfccFilterWeights_(chan, i) = triangle_heights_(chan) *
((upper_(chan) - fftFreqs_(i))/(upper_(chan) - center_(chan)));
}
}
// Initialize MFCC_DCT
float scale_fac = 1.0/ sqrt((double)(totalFilters_/2));
for (j = 0; j<cepstralCoefs_; j++)
for (i=0; i< totalFilters_; i++)
{
mfccDCT_(j, i) = scale_fac * cos(j * (2*i +1) * PI/2/totalFilters_);
if (i == 0)
mfccDCT_(j,i) *= sqrt(2.0)/2.0;
}
// Prepare feature names
featSize_ = outSize_;
featNames_.push_back("MFCC00");
featNames_.push_back("MFCC01");
featNames_.push_back("MFCC02");
featNames_.push_back("MFCC03");
featNames_.push_back("MFCC04");
featNames_.push_back("MFCC05");
featNames_.push_back("MFCC06");
featNames_.push_back("MFCC07");
featNames_.push_back("MFCC08");
featNames_.push_back("MFCC09");
featNames_.push_back("MFCC10");
featNames_.push_back("MFCC11");
featNames_.push_back("MFCC12");
hamming_ = new Hamming(inSize_, zeroSize_);
magfft_ = new MagFFT(inSize_);
windowed.create(inSize_);
magnitude.create(inSize_/2);
fmagnitude.create(inSize_);
earMagnitude_.create(totalFilters_);
}
