不韋 呂 / Mbed 2 deprecated F746_RealtimeSpectrumAnalyzer

Realtime spectrum analyzer. Using FFT, linear prediction, or cepstrum smoothing. Version using MEMS microphone and CODEC, named "F746_RealtimeSpectrumAnalyzer_MEMS_Mic" is registered. リアルタイム スペクトル解析器．解析の手法：FFT，線形予測法，ケプストラムによる平滑化の３種類．このプログラムの説明は，CQ出版社のインターフェース誌，2016年4月号に掲載．外付けのマイクまたは他の信号源等を A0 に接続する．線形予測法，ケプストラムは，スペクトル解析の対象を音声信号に想定してパラメータを設定している．MEMS マイクと CODEC を使ったバージョンを "F746_RealtimeSpectrumAnalyzer_MEMS_Mic" として登録．

Dependencies:   BSP_DISCO_F746NG BUTTON_GROUP LCD_DISCO_F746NG TS_DISCO_F746NG UIT_FFT_Real mbed

MyClasses/LinearPrediction.cpp@18:6630d61aeb3c, 2016-02-22 (annotated)

Committer:
MikamiUitOpen
Date:
Mon Feb 22 13:54:51 2016 +0000
Revision:
18:6630d61aeb3c
Parent:
4:99d4d5ea06a2 
19

Who changed what in which revision?

UserRevisionLine numberNew contents of line
MikamiUitOpen 0:5c237fdcba23 1 //-----------------------------------------------------
MikamiUitOpen 0:5c237fdcba23 2 // Class for linear prediction
MikamiUitOpen 0:5c237fdcba23 3 //
MikamiUitOpen 0:5c237fdcba23 4 // 2015/12/08, Copyright (c) 2015 MIKAMI, Naoki
MikamiUitOpen 0:5c237fdcba23 5 //-----------------------------------------------------
MikamiUitOpen 0:5c237fdcba23 6
MikamiUitOpen 0:5c237fdcba23 7 #include "LinearPrediction.hpp"
MikamiUitOpen 0:5c237fdcba23 8
MikamiUitOpen 0:5c237fdcba23 9 namespace Mikami
MikamiUitOpen 0:5c237fdcba23 10 {
MikamiUitOpen 0:5c237fdcba23 11 LinearPred::LinearPred(int nData, int order)
MikamiUitOpen 0:5c237fdcba23 12 : N_DATA_(nData), ORDER_(order),
MikamiUitOpen 0:5c237fdcba23 13 r_(new float[order+1]), k_(new float[order]),
MikamiUitOpen 0:5c237fdcba23 14 am_(new float[order]) {}
MikamiUitOpen 0:5c237fdcba23 15
MikamiUitOpen 0:5c237fdcba23 16 LinearPred::~LinearPred()
MikamiUitOpen 0:5c237fdcba23 17 {
MikamiUitOpen 0:5c237fdcba23 18 delete[] r_;
MikamiUitOpen 0:5c237fdcba23 19 delete[] k_;
MikamiUitOpen 0:5c237fdcba23 20 delete[] am_;
MikamiUitOpen 0:5c237fdcba23 21 }
MikamiUitOpen 0:5c237fdcba23 22
MikamiUitOpen 0:5c237fdcba23 23 // Calculate linear-predictive coefficients
MikamiUitOpen 0:5c237fdcba23 24 bool LinearPred::Execute(const float x[], float a[],
MikamiUitOpen 0:5c237fdcba23 25 float &em)
MikamiUitOpen 0:5c237fdcba23 26 {
MikamiUitOpen 0:5c237fdcba23 27 AutoCorr(x);
MikamiUitOpen 0:5c237fdcba23 28 return Durbin(a, em);
MikamiUitOpen 0:5c237fdcba23 29 }
MikamiUitOpen 0:5c237fdcba23 30
MikamiUitOpen 0:5c237fdcba23 31 // Calculate auto-correlation
MikamiUitOpen 0:5c237fdcba23 32 void LinearPred::AutoCorr(const float x[])
MikamiUitOpen 0:5c237fdcba23 33 {
MikamiUitOpen 0:5c237fdcba23 34 for (int j=0; j<=ORDER_; j++)
MikamiUitOpen 0:5c237fdcba23 35 {
MikamiUitOpen 0:5c237fdcba23 36 r_[j] = 0.0;
MikamiUitOpen 0:5c237fdcba23 37 for (int n=0; n<N_DATA_-j; n++)
MikamiUitOpen 0:5c237fdcba23 38 r_[j] = r_[j] + x[n]*x[n+j];
MikamiUitOpen 0:5c237fdcba23 39 }
MikamiUitOpen 0:5c237fdcba23 40 }
MikamiUitOpen 0:5c237fdcba23 41
MikamiUitOpen 0:5c237fdcba23 42 // Levinson-Durbin algorithm
MikamiUitOpen 0:5c237fdcba23 43 bool LinearPred::Durbin(float a[], float &em)
MikamiUitOpen 0:5c237fdcba23 44 {
MikamiUitOpen 0:5c237fdcba23 45 // Initialization
MikamiUitOpen 0:5c237fdcba23 46 em = r_[0];
MikamiUitOpen 0:5c237fdcba23 47
MikamiUitOpen 0:5c237fdcba23 48 // Repeat
MikamiUitOpen 0:5c237fdcba23 49 for (int m=0; m<ORDER_; m++)
MikamiUitOpen 0:5c237fdcba23 50 {
MikamiUitOpen 0:5c237fdcba23 51 float w = r_[m+1];
MikamiUitOpen 0:5c237fdcba23 52 for (int j=0; j<=m-1; j++)
MikamiUitOpen 0:5c237fdcba23 53 w = w - r_[m-j]*a[j];
MikamiUitOpen 0:5c237fdcba23 54
MikamiUitOpen 0:5c237fdcba23 55 k_[m] = w/em;
MikamiUitOpen 0:5c237fdcba23 56 em = em*(1 - k_[m]*k_[m]);
MikamiUitOpen 0:5c237fdcba23 57
MikamiUitOpen 0:5c237fdcba23 58 if (em < 0) break; // Error for negative squared sum of residual
MikamiUitOpen 0:5c237fdcba23 59
MikamiUitOpen 0:5c237fdcba23 60 a[m] = k_[m];
MikamiUitOpen 0:5c237fdcba23 61 for (int j=0; j<=m-1; j++)
MikamiUitOpen 0:5c237fdcba23 62 am_[j] = a[j];
MikamiUitOpen 0:5c237fdcba23 63 for (int j=0; j<=m-1; j++)
MikamiUitOpen 0:5c237fdcba23 64 a[j] = am_[j] - k_[m]*am_[m-j-1];
MikamiUitOpen 0:5c237fdcba23 65 }
MikamiUitOpen 0:5c237fdcba23 66
MikamiUitOpen 0:5c237fdcba23 67 if (em < 0) return false;
MikamiUitOpen 0:5c237fdcba23 68 else return true;
MikamiUitOpen 0:5c237fdcba23 69 }
MikamiUitOpen 0:5c237fdcba23 70 }