No photo version of "F746_SpectralAnalysis_Example".
Dependencies: BSP_DISCO_F746NG BUTTON_GROUP LCD_DISCO_F746NG TS_DISCO_F746NG UIT_FFT_Real mbed
SpactrumAnalysisClasses/LinearPrediction.cpp
- Committer:
- MikamiUitOpen
- Date:
- 2015-11-24
- Revision:
- 0:9d7f931c704a
File content as of revision 0:9d7f931c704a:
//----------------------------------------------------- // Class for linear prediction // Copyright (c) 2014 MIKAMI, Naoki, 2014/12/30 //----------------------------------------------------- #include "LinearPrediction.hpp" namespace Mikami { LinearPred::LinearPred(int nData, int order) : N_DATA_(nData), ORDER_(order) { r_ = new float[order+1]; // for auto-correlation k_ = new float[order]; // for PARCOR coefficients am_ = new float[order]; // working area } LinearPred::~LinearPred() { delete[] r_; delete[] k_; delete[] am_; } // Calculate linear-predictive coefficients bool LinearPred::Execute(const float x[], float a[], float &em) { AutoCorr(x); return Durbin(a, em); } // Calculate auto-correlation void LinearPred::AutoCorr(const float x[]) { for (int j=0; j<=ORDER_; j++) { r_[j] = 0.0; for (int n=0; n<N_DATA_-j; n++) r_[j] = r_[j] + x[n]*x[n+j]; } } // Levinson-Durbin algorithm bool LinearPred::Durbin(float a[], float &em) { // Initialization em = r_[0]; // Repeat for (int m=0; m<ORDER_; m++) { float w = r_[m+1]; for (int j=0; j<=m-1; j++) w = w - r_[m-j]*a[j]; k_[m] = w/em; em = em*(1 - k_[m]*k_[m]); if (em < 0) break; // Error for negative squared sum of residual a[m] = k_[m]; for (int j=0; j<=m-1; j++) am_[j] = a[j]; for (int j=0; j<=m-1; j++) a[j] = am_[j] - k_[m]*am_[m-j-1]; } if (em < 0) return false; else return true; } }