不韋 呂 / Mbed 2 deprecated UIT2_SpectrumAnalyzer

Real-time spectrum analyzer for ST Nucleo F401RE using Seeed Studio 2.8'' TFT Touch Shield V2.0.

Dependencies:   SeeedStudioTFTv2 UITDSP_ADDA UIT_FFT_Real mbed

SpactrumAnalysisClasses/LinearPrediction.cpp@0:c5b026c2d07e, 2015-07-26 (annotated)

Committer:
MikamiUitOpen
Date:
Sun Jul 26 02:48:23 2015 +0000
Revision:
0:c5b026c2d07e
1

Who changed what in which revision?

UserRevisionLine numberNew contents of line
MikamiUitOpen 0:c5b026c2d07e 1 //-----------------------------------------------------
MikamiUitOpen 0:c5b026c2d07e 2 // Class for linear prediction
MikamiUitOpen 0:c5b026c2d07e 3 // Copyright (c) 2014 MIKAMI, Naoki, 2014/12/30
MikamiUitOpen 0:c5b026c2d07e 4 //-----------------------------------------------------
MikamiUitOpen 0:c5b026c2d07e 5
MikamiUitOpen 0:c5b026c2d07e 6 #include "LinearPrediction.hpp"
MikamiUitOpen 0:c5b026c2d07e 7
MikamiUitOpen 0:c5b026c2d07e 8 namespace Mikami
MikamiUitOpen 0:c5b026c2d07e 9 {
MikamiUitOpen 0:c5b026c2d07e 10 LinearPred::LinearPred(int nData, int order)
MikamiUitOpen 0:c5b026c2d07e 11 : N_DATA_(nData), ORDER_(order)
MikamiUitOpen 0:c5b026c2d07e 12 {
MikamiUitOpen 0:c5b026c2d07e 13 r_ = new float[order+1]; // for auto-correlation
MikamiUitOpen 0:c5b026c2d07e 14 k_ = new float[order]; // for PARCOR coefficients
MikamiUitOpen 0:c5b026c2d07e 15 am_ = new float[order]; // working area
MikamiUitOpen 0:c5b026c2d07e 16 }
MikamiUitOpen 0:c5b026c2d07e 17
MikamiUitOpen 0:c5b026c2d07e 18 LinearPred::~LinearPred()
MikamiUitOpen 0:c5b026c2d07e 19 {
MikamiUitOpen 0:c5b026c2d07e 20 delete[] r_;
MikamiUitOpen 0:c5b026c2d07e 21 delete[] k_;
MikamiUitOpen 0:c5b026c2d07e 22 delete[] am_;
MikamiUitOpen 0:c5b026c2d07e 23 }
MikamiUitOpen 0:c5b026c2d07e 24
MikamiUitOpen 0:c5b026c2d07e 25 // Calculate linear-predictive coefficients
MikamiUitOpen 0:c5b026c2d07e 26 bool LinearPred::Execute(const float x[], float a[],
MikamiUitOpen 0:c5b026c2d07e 27 float &em)
MikamiUitOpen 0:c5b026c2d07e 28 {
MikamiUitOpen 0:c5b026c2d07e 29 AutoCorr(x);
MikamiUitOpen 0:c5b026c2d07e 30 return Durbin(a, em);
MikamiUitOpen 0:c5b026c2d07e 31 }
MikamiUitOpen 0:c5b026c2d07e 32
MikamiUitOpen 0:c5b026c2d07e 33 // Calculate auto-correlation
MikamiUitOpen 0:c5b026c2d07e 34 void LinearPred::AutoCorr(const float x[])
MikamiUitOpen 0:c5b026c2d07e 35 {
MikamiUitOpen 0:c5b026c2d07e 36 for (int j=0; j<=ORDER_; j++)
MikamiUitOpen 0:c5b026c2d07e 37 {
MikamiUitOpen 0:c5b026c2d07e 38 r_[j] = 0.0;
MikamiUitOpen 0:c5b026c2d07e 39 for (int n=0; n<N_DATA_-j; n++)
MikamiUitOpen 0:c5b026c2d07e 40 r_[j] = r_[j] + x[n]*x[n+j];
MikamiUitOpen 0:c5b026c2d07e 41 }
MikamiUitOpen 0:c5b026c2d07e 42 }
MikamiUitOpen 0:c5b026c2d07e 43
MikamiUitOpen 0:c5b026c2d07e 44 // Levinson-Durbin algorithm
MikamiUitOpen 0:c5b026c2d07e 45 bool LinearPred::Durbin(float a[], float &em)
MikamiUitOpen 0:c5b026c2d07e 46 {
MikamiUitOpen 0:c5b026c2d07e 47 // Initialization
MikamiUitOpen 0:c5b026c2d07e 48 em = r_[0];
MikamiUitOpen 0:c5b026c2d07e 49
MikamiUitOpen 0:c5b026c2d07e 50 // Repeat
MikamiUitOpen 0:c5b026c2d07e 51 for (int m=0; m<ORDER_; m++)
MikamiUitOpen 0:c5b026c2d07e 52 {
MikamiUitOpen 0:c5b026c2d07e 53 float w = r_[m+1];
MikamiUitOpen 0:c5b026c2d07e 54 for (int j=0; j<=m-1; j++)
MikamiUitOpen 0:c5b026c2d07e 55 w = w - r_[m-j]*a[j];
MikamiUitOpen 0:c5b026c2d07e 56
MikamiUitOpen 0:c5b026c2d07e 57 k_[m] = w/em;
MikamiUitOpen 0:c5b026c2d07e 58 em = em*(1 - k_[m]*k_[m]);
MikamiUitOpen 0:c5b026c2d07e 59
MikamiUitOpen 0:c5b026c2d07e 60 if (em < 0) break; // Error for negative squared sum of residual
MikamiUitOpen 0:c5b026c2d07e 61
MikamiUitOpen 0:c5b026c2d07e 62 a[m] = k_[m];
MikamiUitOpen 0:c5b026c2d07e 63 for (int j=0; j<=m-1; j++)
MikamiUitOpen 0:c5b026c2d07e 64 am_[j] = a[j];
MikamiUitOpen 0:c5b026c2d07e 65 for (int j=0; j<=m-1; j++)
MikamiUitOpen 0:c5b026c2d07e 66 a[j] = am_[j] - k_[m]*am_[m-j-1];
MikamiUitOpen 0:c5b026c2d07e 67 }
MikamiUitOpen 0:c5b026c2d07e 68
MikamiUitOpen 0:c5b026c2d07e 69 if (em < 0) return false;
MikamiUitOpen 0:c5b026c2d07e 70 else return true;
MikamiUitOpen 0:c5b026c2d07e 71 }
MikamiUitOpen 0:c5b026c2d07e 72 }