最近在写一些数据处理的程序。经常需要对数据进行平滑处理。直接用FIR滤波器或IIR滤波器都有一个启动问题,滤波完成后总要对数据掐头去尾。因此去找了些简单的数据平滑处理的方法。
在一本老版本的《数学手册》中找到了几个基于最小二乘法的数据平滑算法。将其写成了C 代码,测试了一下,效果还可以。这里简单的记录一下,算是给自己做个笔记。
算法的原理很简单,以五点三次平滑为例。取相邻的5个数据点,可以拟合出一条3次曲线来,然后用3次曲线上相应的位置的数据值作为滤波后结果。简单的说就是 Savitzky-Golay 滤波器 。只不过Savitzky-Golay 滤波器并不特殊考虑边界的几个数据点,而这个算法还特意把边上的几个点的数据拟合结果给推导了出来。
不多说了,下面贴代码。首先是线性拟合平滑处理的代码. 分别为三点线性平滑、五点线性平滑和七点线性平滑。
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voidlinearSmooth3 ( double in[], double out[], int N ) { int i; if ( N < 3 ) { for ( i = 0; i <= N - 1; i++ ) { out[i] = in[i]; } } else { out[0] = ( 5.0 * in[0] + 2.0 * in[1] - in[2] ) / 6.0;
for ( i = 1; i <= N - 2; i++ ) { out[i] = ( in[i - 1] + in[i] + in[i + 1] ) / 3.0; }
out[N - 1] = ( 5.0 * in[N - 1] + 2.0 * in[N - 2] - in[N - 3] ) / 6.0; } }
voidlinearSmooth5 ( double in[], double out[], int N ) { int i; if ( N < 5 ) { for ( i = 0; i <= N - 1; i++ ) { out[i] = in[i]; } } else { out[0] = ( 3.0 * in[0] + 2.0 * in[1] + in[2] - in[4] ) / 5.0; out[1] = ( 4.0 * in[0] + 3.0 * in[1] + 2 * in[2] + in[3] ) / 10.0; for ( i = 2; i <= N - 3; i++ ) { out[i] = ( in[i - 2] + in[i - 1] + in[i] + in[i + 1] + in[i + 2] ) / 5.0; } out[N - 2] = ( 4.0 * in[N - 1] + 3.0 * in[N - 2] + 2 * in[N - 3] + in[N - 4] ) / 10.0; out[N - 1] = ( 3.0 * in[N - 1] + 2.0 * in[N - 2] + in[N - 3] - in[N - 5] ) / 5.0; } }
voidlinearSmooth7 ( double in[], double out[], int N ) { int i; if ( N < 7 ) { for ( i = 0; i <= N - 1; i++ ) { out[i] = in[i]; } } else { out[0] = ( 13.0 * in[0] + 10.0 * in[1] + 7.0 * in[2] + 4.0 * in[3] + in[4] - 2.0 * in[5] - 5.0 * in[6] ) / 28.0;
out[1] = ( 5.0 * in[0] + 4.0 * in[1] + 3 * in[2] + 2 * in[3] + in[4] - in[5] ) / 14.0;
out[2] = ( 7.0 * in[0] + 6.0 * in [1] + 5.0 * in[2] + 4.0 * in[3] + 3.0 * in[4] + 2.0 * in[5] + in[6] ) / 28.0;
for ( i = 3; i <= N - 4; i++ ) { out[i] = ( in[i - 3] + in[i - 2] + in[i - 1] + in[i] + in[i + 1] + in[i + 2] + in[i + 3] ) / 7.0; }
out[N - 3] = ( 7.0 * in[N - 1] + 6.0 * in [N - 2] + 5.0 * in[N - 3] + 4.0 * in[N - 4] + 3.0 * in[N - 5] + 2.0 * in[N - 6] + in[N - 7] ) / 28.0;
out[N - 2] = ( 5.0 * in[N - 1] + 4.0 * in[N - 2] + 3.0 * in[N - 3] + 2.0 * in[N - 4] + in[N - 5] - in[N - 6] ) / 14.0;
out[N - 1] = ( 13.0 * in[N - 1] + 10.0 * in[N - 2] + 7.0 * in[N - 3] + 4 * in[N - 4] + in[N - 5] - 2 * in[N - 6] - 5 * in[N - 7] ) / 28.0; } } |
然后是利用二次函数拟合平滑。
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voidquadraticSmooth5(double in[], double out[], int N) { int i; if ( N < 5 ) { for ( i = 0; i <= N - 1; i++ ) { out[i] = in[i]; } } else { out[0] = ( 31.0 * in[0] + 9.0 * in[1] - 3.0 * in[2] - 5.0 * in[3] + 3.0 * in[4] ) / 35.0; out[1] = ( 9.0 * in[0] + 13.0 * in[1] + 12 * in[2] + 6.0 * in[3] - 5.0 *in[4]) / 35.0; for ( i = 2; i <= N - 3; i++ ) { out[i] = ( - 3.0 * (in[i - 2] + in[i + 2]) + 12.0 * (in[i - 1] + in[i + 1]) + 17 * in[i] ) / 35.0; } out[N - 2] = ( 9.0 * in[N - 1] + 13.0 * in[N - 2] + 12.0 * in[N - 3] + 6.0 * in[N - 4] - 5.0 * in[N - 5] ) / 35.0; out[N - 1] = ( 31.0 * in[N - 1] + 9.0 * in[N - 2] - 3.0 * in[N - 3] - 5.0 * in[N - 4] + 3.0 * in[N - 5]) / 35.0; } }
voidquadraticSmooth7(double in[], double out[], int N) { int i; if ( N < 7 ) { for ( i = 0; i <= N - 1; i++ ) { out[i] = in[i]; } } else { out[0] = ( 5.0 * in[0] + 15.0 * in[1] + 3.0 * in[2] - 4.0 * in[3] - 6.0 * in[4] - 3.0 * in[5] + 5.0 * in[6] ) / 42.0;
out[1] = ( 5.0 * in[0] + 4.0 * in[1] + 3.0 * in[2] + 2.0 * in[3] + in[4] - in[5] ) / 14.0;
out[2] = ( 1.0 * in[0] + 3.0 * in [1] + 4.0 * in[2] + 4.0 * in[3] + 3.0 * in[4] + 1.0 * in[5] - 2.0 * in[6] ) / 14.0; for ( i = 3; i <= N - 4; i++ ) { out[i] = ( -2.0 * (in[i - 3] + in[i + 3]) + 3.0 * (in[i - 2] + in[i + 2]) + 6.0 * (in[i - 1] + in[i + 1]) + 7.0 * in[i] ) / 21.0; } out[N - 3] = ( 1.0 * in[N - 1] + 3.0 * in [N - 2] + 4.0 * in[N - 3] + 4.0 * in[N - 4] + 3.0 * in[N - 5] + 1.0 * in[N - 6] - 2.0 * in[N - 7] ) / 14.0;
out[N - 2] = ( 5.0 * in[N - 1] + 4.0 * in[N - 2] + 3.0 * in[N - 3] + 2.0 * in[N - 4] + in[N - 5] - in[N - 6] ) / 14.0;
out[N - 1] = ( 32.0 * in[N - 1] + 15.0 * in[N - 2] + 3.0 * in[N - 3] - 4.0 * in[N - 4] - 6.0 * in[N - 5] - 3.0 * in[N - 6] + 5.0 * in[N - 7] ) / 42.0; } } |
最后是三次函数拟合平滑。
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/** * 五点三次平滑 * */ voidcubicSmooth5 ( double in[], double out[], int N ) {
int i; if ( N < 5 ) { for ( i = 0; i <= N - 1; i++ ) out[i] = in[i]; }
else { out[0] = (69.0 * in[0] + 4.0 * in[1] - 6.0 * in[2] + 4.0 * in[3] - in[4]) / 70.0; out[1] = (2.0 * in[0] + 27.0 * in[1] + 12.0 * in[2] - 8.0 * in[3] + 2.0 * in[4]) / 35.0; for ( i = 2; i <= N - 3; i++ ) { out[i] = (-3.0 * (in[i - 2] + in[i + 2])+ 12.0 * (in[i - 1] + in[i + 1]) + 17.0 * in[i] ) / 35.0; } out[N - 2] = (2.0 * in[N - 5] - 8.0 * in[N - 4] + 12.0 * in[N - 3] + 27.0 * in[N - 2] + 2.0 * in[N - 1]) / 35.0; out[N - 1] = (- in[N - 5] + 4.0 * in[N - 4] - 6.0 * in[N - 3] + 4.0 * in[N - 2] + 69.0 * in[N - 1]) / 70.0; } return; }
voidcubicSmooth7(double in[], double out[], int N) { int i; if ( N < 7 ) { for ( i = 0; i <= N - 1; i++ ) { out[i] = in[i]; } } else { out[0] = ( 39.0 * in[0] + 8.0 * in[1] - 4.0 * in[2] - 4.0 * in[3] + 1.0 * in[4] + 4.0 * in[5] - 2.0 * in[6] ) / 42.0; out[1] = ( 8.0 * in[0] + 19.0 * in[1] + 16.0 * in[2] + 6.0 * in[3] - 4.0 * in[4] - 7.0* in[5] + 4.0 * in[6] ) / 42.0; out[2] = ( -4.0 * in[0] + 16.0 * in [1] + 19.0 * in[2] + 12.0 * in[3] + 2.0 * in[4] - 4.0 * in[5] + 1.0 * in[6] ) / 42.0; for ( i = 3; i <= N - 4; i++ ) { out[i] = ( -2.0 * (in[i - 3] + in[i + 3]) + 3.0 * (in[i - 2] + in[i + 2]) + 6.0 * (in[i - 1] + in[i + 1]) + 7.0 * in[i] ) / 21.0; } out[N - 3] = ( -4.0 * in[N - 1] + 16.0 * in [N - 2] + 19.0 * in[N - 3] + 12.0 * in[N - 4] + 2.0 * in[N - 5] - 4.0 * in[N - 6] + 1.0 * in[N - 7] ) / 42.0; out[N - 2] = ( 8.0 * in[N - 1] + 19.0 * in[N - 2] + 16.0 * in[N - 3] + 6.0 * in[N - 4] - 4.0 * in[N - 5] - 7.0 * in[N - 6] + 4.0 * in[N - 7] ) / 42.0; out[N - 1] = ( 39.0 * in[N - 1] + 8.0 * in[N - 2] - 4.0 * in[N - 3] - 4.0 * in[N - 4] + 1.0 * in[N - 5] + 4.0 * in[N - 6] - 2.0 * in[N - 7] ) / 42.0; } } |