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在学习信号处理的时候，线性预测是一个比较难理解的知识点，为了加快很多朋友的理解，这里给出Levinson-Durbin算法的线性预测实现和一个测试Demo，Demo中很明确的把输入信号、预测信号、预测误差打印了出来，这样就能以最直观的方式，把线性预测的实现与作用展示出来。话不多说，直接上代码！
[html] view plain copy typedef float OsFlt32; typedef int OsInt32; OsFlt32 lpc(const OsFlt32 *r,OsInt32 p,OsFlt32 *a) { OsInt32 i,j; OsFlt32 err; if(0 == r[0]) { for(i = 0; i < p; i++) a[i] = 0; return 0; } a[0] = 1.0; err = r[0]; for(i = 0; i < p; i++) { OsFlt32 lambda = 0.0; for(j = 0; j <= i; j++) lambda -= a[j]*r[i+1-j]; lambda /= err; // Update LPC coefficients and total error for(j = 0; j <= (i+1)/2; j++) { OsFlt32 temp = a[i+1-j] + lambda * a[j]; a[j] = a[j] + lambda * a[i+1-j]; a[i+1-j] = temp; } err *= (1.0 - lambda*lambda); } return err; } void autocorr(const OsFlt32 *x,OsInt32 n,OsFlt32 *r,OsInt32 k) { OsFlt32 d; OsInt32 i,p; for(p = 0; p <= k; p++) { for(i = 0,d = 0.0; i < n-p; i++) d += x[i] * x[i+p]; r[p] = d; } } [html] view plain copy #include "lpc.h" int main(int argc,char **argv) { OsInt32 nLen = 128; OsFlt32 *pOriginal,*pPRedicted; OsInt32 i,j; const OsInt32 order = 4; OsFlt32 R[order+1] = {0.0}; OsFlt32 A[order+1] = {0.0}; OsFlt32 error; pOriginal = (OsFlt32*)calloc(nLen,sizeof(OsFlt32)); pPredicted = (OsFlt32*)calloc(nLen,sizeof(OsFlt32)); for(i = 0; i < nLen; i++) pOriginal[i] = sin(i*0.01) + 0.75 * sin(i*0.03) + 0.5 * sin(i*0.05) + 0.25 * sin(i*0.11); autocorr(pOriginal,nLen,R,order); lpc(R,order,A); for(i = 1; i <= order; i++) A[i-1] = A[i]; for(i = order; i < nLen; i++) { pPredicted[i] = 0.0; for(j = 0; j < order; j++) pPredicted[i] -= A[j] * pOriginal[i-1-j]; } error = 0; for(i = order; i < nLen; i++) { double delta = pPredicted[i] - pOriginal[i]; printf( "Index: %.2d / Original: %.6f / Predicted: %.6f/n",i,pOriginal[i],pPredicted[i]); error += delta * delta; } printf("Forward Linear Prediction Approximation Error: %f/n",error); free(pPredicted); free(pOriginal); return 0; }新闻热点
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