使用fopen_s怎么求wav的时域信号均值、均方值、方差，计算信号的自协方差矩阵和功率谱

以下是使用fopen_s函数求wav文件的时域信号均值、均方值、方差，计算信号的自协方差矩阵和功率谱的示例代码：

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>

#define HEADER_SIZE 44

// 计算时域信号均值
double mean(double* signal, int length) {
    double sum = 0;
    for (int i = 0; i < length; i++) {
        sum += signal[i];
    }
    return sum / length;
}

// 计算时域信号均方值
double rms(double* signal, int length) {
    double sum = 0;
    for (int i = 0; i < length; i++) {
        sum += pow(signal[i], 2);
    }
    return sqrt(sum / length);
}

// 计算时域信号方差
double variance(double* signal, int length) {
    double m = mean(signal, length);
    double sum = 0;
    for (int i = 0; i < length; i++) {
        sum += pow(signal[i] - m, 2);
    }
    return sum / length;
}

// 计算自协方差矩阵
void autocovariance(double* signal, int length, double** cov) {
    for (int i = 0; i < length; i++) {
        for (int j = 0; j < length; j++) {
            cov[i][j] = 0;
            for (int k = 0; k < length - j; k++) {
                cov[i][j] += signal[k] * signal[k + j];
            }
            cov[i][j] /= length;
        }
    }
}

// 计算功率谱
void power_spectrum(double* signal, int length, double* spectrum) {
    int n = length / 2 + 1;
    double* fft_real = (double*)malloc(sizeof(double) * length);
    double* fft_imag = (double*)malloc(sizeof(double) * length);
    memset(fft_imag, 0, sizeof(double) * length);

    // 做FFT变换
    for (int i = 0; i < length; i++) {
        fft_real[i] = signal[i];
    }
    rfft(fft_real, fft_imag, length, FFT_FORWARD);

    // 计算功率谱
    for (int i = 0; i < n; i++) {
        spectrum[i] = pow(fft_real[i], 2) + pow(fft_imag[i], 2);
    }

    free(fft_real);
    free(fft_imag);
}

int main() {
    char filename[] = "test.wav";
    FILE* fp;
    fopen_s(&fp, filename, "rb");

    if (!fp) {
        printf("Open file failed!\n");
        return -1;
    }

    // 读取wav文件头
    char header[HEADER_SIZE];
    fread(header, 1, HEADER_SIZE, fp);

    // 读取wav文件数据
    int data_size = *(int*)(header + 40);
    int sample_rate = *(int*)(header + 24);
    int bit_depth = *(short*)(header + 34) / 8;
    int sample_count = data_size / bit_depth;
    double* signal = (double*)malloc(sizeof(double) * sample_count);
    fread(signal, bit_depth, sample_count, fp);

    // 计算时域信号均值、均方值、方差
    double m = mean(signal, sample_count);
    double r = rms(signal, sample_count);
    double v = variance(signal, sample_count);
    printf("mean: %f\n", m);
    printf("rms: %f\n", r);
    printf("variance: %f\n", v);

    // 计算自协方差矩阵
    double** cov = (double**)malloc(sizeof(double*) * sample_count);
    for (int i = 0; i < sample_count; i++) {
        cov[i] = (double*)malloc(sizeof(double) * sample_count);
    }
    autocovariance(signal, sample_count, cov);

    // 计算功率谱
    int n = sample_count / 2 + 1;
    double* spectrum = (double*)malloc(sizeof(double) * n);
    power_spectrum(signal, sample_count, spectrum);
    for (int i = 0; i < n; i++) {
        printf("spectrum[%d]: %f\n", i, spectrum[i]);
    }

    // 释放内存
    free(signal);
    for (int i = 0; i < sample_count; i++) {
        free(cov[i]);
    }
    free(cov);
    free(spectrum);

    fclose(fp);

    return 0;
}

需要注意的是，这份代码中调用了一个rfft函数来进行FFT计算，这个函数的实现可以参考另一篇文章：https://blog.csdn.net/qq_37385726/article/details/107813917