Realtime sound spectrogram using FFT or linear prediction. Spectrogram is displayed on the display of PC. リアルタイム・スペクトログラム.解析の手法:FFT,線形予測法.スペクトログラムは PC のディスプレー装置に表示される.PC 側のプログラム:F446_Spectrogram.
Dependencies: Array_Matrix mbed SerialTxRxIntr F446_AD_DA UIT_FFT_Real
MySpectrogram/LinearPrediction.cpp
- Committer:
- MikamiUitOpen
- Date:
- 2017-02-17
- Revision:
- 0:a539141b9dec
File content as of revision 0:a539141b9dec:
//----------------------------------------------------- // Class for linear prediction // // 2017/02/11, Copyright (c) 2017 MIKAMI, Naoki //----------------------------------------------------- #include "LinearPrediction.hpp" namespace Mikami { LinearPred::LinearPred(int nData, int order) : N_DATA_(nData), order_(order), r_(order+1), k_(order), am_(order) {} // 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; } }