【STM32H7S78-DK】测评+自适应滤波器计算速度测评
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ARM DSP 库提供了 LMS 最小均方自适应滤波和归一化最小均方自适应滤波器，自适应滤波器能够根据输入信号自动调整滤波系数进行数字滤波。对于一些应用来说，由于事先并不知道需要进行操作的参数，例如一些噪声信号的特性，所以要求 使用自适应的系数进行处理。在这种情况下，通常使用自适应滤波器，自适应滤波器使用反馈来调整滤 波器系数以及频率响应。 随着处理器性能的增强，自适应滤波器的应用越来越常见，STM32H7S78具有高性能的DSP运算性能，本帖将在STM32H7S78测试自适应滤波器的性能。
测试代码参考了大佬们的分享，
#include "arm_math.h"
#include "arm_const_structs.h"
#define TEST_LENGTH_SAMPLES 2048 /* 采样点数 */
#define BLOCK_SIZE 2048 /* 调用一次arm_lms_norm_f32处理的采样点个数 */
#define NUM_TAPS 20 /* 滤波器系数个数 */
uint32_t blockSize = BLOCK_SIZE;
uint32_t numBlocks = TEST_LENGTH_SAMPLES/BLOCK_SIZE; /* 需要调用arm_lms_norm_f32的次数 */
static float32_t testInput_f32_50Hz_200Hz[TEST_LENGTH_SAMPLES]={0}; /* 源波形 */
static float32_t testInput_f32_REF[TEST_LENGTH_SAMPLES]={0}; /* 参考波形 */
static float32_t test_f32_ERR[TEST_LENGTH_SAMPLES]={0}; /* 误差数据 */
static float32_t testOutput[TEST_LENGTH_SAMPLES]={0}; /* 滤波后的输出 */
static float32_t lmsStateF32[BLOCK_SIZE + NUM_TAPS - 1]={0}; /* 状态缓存，大小numTaps + blockSize - 1 */
static float32_t lmsCoeffs32[NUM_TAPS] = {0}; /* 滤波器系数 */
/* 测试数据 */
const float32_t OrigalData1[2048]= {
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6.058343,
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//原始波形由任意波形+ 高斯分布白噪声 + 均匀分布白噪声组成，滤除高斯分布白噪声 + 均匀分布白噪声。
void arm_lms_f32_test2(void)
{
uint32_t i;
arm_lms_norm_instance_f32 lmsS;
float32_t *inputF32, *outputF32, *inputREF, *outputERR;
/* 如果是实时性的滤波，仅需清零一次 */
memset(lmsCoeffs32,0,sizeof(lmsCoeffs32));
memset(lmsStateF32,0,sizeof(lmsStateF32));
/* 初始化输入输出缓存指针 */
inputF32 = (float32_t *)&MixData[0]; /* 原始波形 */
outputF32 = (float32_t *)&testOutput[0]; /* 滤波后输出波形 */
inputREF = (float32_t *)&OrigalData[0]; /* 参考波形 */
outputERR = (float32_t *)&test_f32_ERR[0]; /* 误差数据 */
/* 归一化LMS初始化 */
arm_lms_norm_init_f32 (&lmsS, /* LMS结构体 */
NUM_TAPS, /* 滤波器系数个数 */
(float32_t *)&lmsCoeffs32[0], /* 滤波 */
&lmsStateF32[0], /* 滤波器系数 */
0.01, /* 步长 */
blockSize); /* 处理的数据个数 */
/* 实现LMS自适应滤波，这里每次处理1个点 */
for(i=0; i < numBlocks; i++)
{
arm_lms_norm_f32(&lmsS, /* LMS结构体 */
inputF32 + (i * blockSize), /* 输入数据 */
inputREF + (i * blockSize), /* 输出数据 */
outputF32 + (i * blockSize), /* 参考数据 */
outputERR + (i * blockSize), /* 误差数据 */
blockSize); /* 处理的数据个数 */
}
/* 打印滤波后结果 */
for(i=0; i<TEST_LENGTH_SAMPLES; i++)
{
printf("%f, %f, %f\r\n", MixData[i], outputF32[i], test_f32_ERR[i]);
}
}
图中红色信号是原始测试波形数据，绿色是滤波后数据，可见噪声毛刺基本被滤除，
性能
计算2048点自适应滤波耗时180个时钟周期，主频配置的是600MHz，即1/600*180=0.3us，足以满足一般实时性要求较高的场合。
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