谁能告诉我如何使用 c 编程语言实现 FIR 滤波器。
3 回答
设计 FIR 滤波器不是一个简单的话题,但实现一个已经设计好的滤波器(假设你已经有了 FIR 系数)也不错。该算法称为卷积。这是一个天真的实现......
void convolve (double *p_coeffs, int p_coeffs_n,
double *p_in, double *p_out, int n)
{
int i, j, k;
double tmp;
for (k = 0; k < n; k++) // position in output
{
tmp = 0;
for (i = 0; i < p_coeffs_n; i++) // position in coefficients array
{
j = k - i; // position in input
if (j >= 0) // bounds check for input buffer
{
tmp += p_coeffs [i] * p_in [j];
}
}
p_out [k] = tmp;
}
}
基本上,卷积对输入信号进行移动加权平均。权重是滤波器系数,假设总和为 1.0。如果权重总和不是 1.0,则会得到一些放大/衰减以及滤波。
顺便说一句 - 这个函数可能有向后的系数数组 - 我没有仔细检查过,我已经有一段时间没有考虑这些事情了。
对于如何计算特定滤波器的 FIR 系数,背后有相当多的数学知识——你真的需要一本关于数字信号处理的好书。这个是免费的PDF,但我不确定它有多好。我有Rorabaugh和Orfandis,都在九十年代中期出版,但这些东西并没有真正过时。
要组合多个过滤器:
从单位脉冲开始(第一个位置为 1,其他位置为 0 的信号)。应用第一个过滤器。应用第二个过滤器。继续,直到应用所有过滤器。结果显示了组合滤波器如何对单位脉冲进行卷积(假设数组足够长以至于没有数据丢失),因此其中的值是一个滤波器的系数,它是其他滤波器的组合。
这是示例代码:
#include <stdio.h>
#include <string.h>
#define NumberOf(a) (sizeof (a) / sizeof *(a))
/* Convolve Signal with Filter.
Signal must contain OutputLength + FilterLength - 1 elements. Conversely,
if there are N elements in Signal, OutputLength may be at most
N+1-FilterLength.
*/
static void convolve(
float *Signal,
float *Filter, size_t FilterLength,
float *Output, size_t OutputLength)
{
for (size_t i = 0; i < OutputLength; ++i)
{
double sum = 0;
for (size_t j = 0; j < FilterLength; ++j)
sum += Signal[i+j] * Filter[FilterLength - 1 - j];
Output[i] = sum;
}
}
int main(void)
{
// Define a length for buffers that is long enough for this demonstration.
#define LongEnough 128
// Define some sample filters.
float Filter0[] = { 1, 2, -1 };
float Filter1[] = { 1, 5, 7, 5, 1 };
size_t Filter0Length = NumberOf(Filter0);
size_t Filter1Length = NumberOf(Filter1);
// Define a unit impulse positioned so it captures all of the filters.
size_t UnitImpulsePosition = Filter0Length - 1 + Filter1Length - 1;
float UnitImpulse[LongEnough];
memset(UnitImpulse, 0, sizeof UnitImpulse);
UnitImpulse[UnitImpulsePosition] = 1;
// Calculate a filter that is Filter0 and Filter1 combined.
float CombinedFilter[LongEnough];
// Set N to number of inputs that must be used.
size_t N = UnitImpulsePosition + 1 + Filter0Length - 1 + Filter1Length - 1;
// Subtract to find number of outputs of first convolution, then convolve.
N -= Filter0Length - 1;
convolve(UnitImpulse, Filter0, Filter0Length, CombinedFilter, N);
// Subtract to find number of outputs of second convolution, then convolve.
N -= Filter1Length - 1;
convolve(CombinedFilter, Filter1, Filter1Length, CombinedFilter, N);
// Remember size of resulting filter.
size_t CombinedFilterLength = N;
// Display filter.
for (size_t i = 0; i < CombinedFilterLength; ++i)
printf("CombinedFilter[%zu] = %g.\n", i, CombinedFilter[i]);
// Define two identical signals.
float Buffer0[LongEnough];
float Buffer1[LongEnough];
for (size_t i = 0; i < LongEnough; ++i)
{
Buffer0[i] = i;
Buffer1[i] = i;
}
// Convolve Buffer0 by using the two filters separately.
// Start with buffer length.
N = LongEnough;
// Subtract to find number of outputs of first convolution, then convolve.
N -= Filter0Length - 1;
convolve(Buffer0, Filter0, Filter0Length, Buffer0, N);
// Subtract to find number of outputs of second convolution, then convolve.
N -= Filter1Length - 1;
convolve(Buffer0, Filter1, Filter1Length, Buffer0, N);
// Remember the length of the result.
size_t ResultLength = N;
// Convolve Buffer1 with the combined filter.
convolve(Buffer1, CombinedFilter, CombinedFilterLength, Buffer1, ResultLength);
// Show the contents of Buffer0 and Buffer1, and their differences.
for (size_t i = 0; i < ResultLength; ++i)
{
printf("Buffer0[%zu] = %g. Buffer1[%zu] = %g. Difference = %g.\n",
i, Buffer0[i], i, Buffer1[i], Buffer0[i] - Buffer1[i]);
}
return 0;
}
我发现这个代码片段对我不起作用(Visual Studio 2005)。
我最终确实发现卷积问题有一个很好的答案:
对于那些不知道的人 - 卷积与 FIR 滤波的操作完全相同 - “内核”是 FIR 滤波器脉冲响应,信号是输入信号。
我希望这可以帮助一些正在寻找 FIR 代码的可怜的 sap :-)