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

要计算wav文件的时域信号均值、均方值、方差，可以使用以下代码：

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

#define BUFFER_SIZE 4096

int main()
{
    FILE *file = NULL;
    fopen_s(&file, "audio.wav", "rb");

    if (file == NULL)
    {
        printf("Failed to open file.\n");
        return 1;
    }

    // 读取文件头
    char riff[4], wave[4], fmt[4], data[4];
    unsigned int fileSize, fmtSize, numChannels, sampleRate, byteRate, blockAlign, bitsPerSample, dataSize;

    fread(riff, sizeof(char), 4, file);
    fread(&fileSize, sizeof(unsigned int), 1, file);
    fread(wave, sizeof(char), 4, file);
    fread(fmt, sizeof(char), 4, file);
    fread(&fmtSize, sizeof(unsigned int), 1, file);
    fread(&numChannels, sizeof(unsigned short), 1, file);
    fread(&sampleRate, sizeof(unsigned int), 1, file);
    fread(&byteRate, sizeof(unsigned int), 1, file);
    fread(&blockAlign, sizeof(unsigned short), 1, file);
    fread(&bitsPerSample, sizeof(unsigned short), 1, file);
    fread(data, sizeof(char), 4, file);
    fread(&dataSize, sizeof(unsigned int), 1, file);

    // 计算均值、均方值、方差
    int buffer[BUFFER_SIZE];
    int numSamples = dataSize / (bitsPerSample / 8);
    double mean = 0.0, rms = 0.0, variance = 0.0;

    for (int i = 0; i < numSamples; i += BUFFER_SIZE)
    {
        int numSamplesToRead = BUFFER_SIZE;
        if (i + numSamplesToRead > numSamples)
        {
            numSamplesToRead = numSamples - i;
        }

        fread(buffer, sizeof(int), numSamplesToRead, file);

        for (int j = 0; j < numSamplesToRead; j++)
        {
            mean += (double)buffer[j] / (double)numSamples;
            rms += pow((double)buffer[j], 2.0) / (double)numSamples;
        }
    }

    fseek(file, sizeof(char) * 44, SEEK_SET);

    for (int i = 0; i < numSamples; i += BUFFER_SIZE)
    {
        int numSamplesToRead = BUFFER_SIZE;
        if (i + numSamplesToRead > numSamples)
        {
            numSamplesToRead = numSamples - i;
        }

        fread(buffer, sizeof(int), numSamplesToRead, file);

        for (int j = 0; j < numSamplesToRead; j++)
        {
            variance += pow((double)buffer[j] - mean, 2.0) / (double)numSamples;
        }
    }

    rms = sqrt(rms);
    variance = sqrt(variance);

    printf("Mean: %f\n", mean);
    printf("RMS: %f\n", rms);
    printf("Variance: %f\n", variance);

    // 计算自协方差矩阵
    double autocovariance[numSamples];
    for (int k = 0; k < numSamples; k++)
    {
        double sum = 0.0;

        for (int i = 0; i < numSamples - k; i += BUFFER_SIZE)
        {
            int numSamplesToRead = BUFFER_SIZE;
            if (i + numSamplesToRead > numSamples - k)
            {
                numSamplesToRead = numSamples - k - i;
            }

            fread(buffer, sizeof(int), numSamplesToRead, file);

            for (int j = 0; j < numSamplesToRead; j++)
            {
                sum += ((double)buffer[j] - mean) * ((double)buffer[j + k] - mean) / (double)numSamples;
            }
        }

        autocovariance[k] = sum;
    }

    // 计算功率谱
    double powerSpectrum[numSamples / 2];
    for (int i = 0; i < numSamples / 2; i++)
    {
        double sum = 0.0;

        for (int j = 0; j < numSamples; j += BUFFER_SIZE)
        {
            int numSamplesToRead = BUFFER_SIZE;
            if (j + numSamplesToRead > numSamples)
            {
                numSamplesToRead = numSamples - j;
            }

            fread(buffer, sizeof(int), numSamplesToRead, file);

            for (int k = 0; k < numSamplesToRead; k++)
            {
                sum += ((double)buffer[k] * cos(2.0 * M_PI * i * k / (double)numSamples) +
                        (double)buffer[k] * sin(2.0 * M_PI * i * k / (double)numSamples)) / (double)numSamples;
            }
        }

        powerSpectrum[i] = pow(sum, 2.0);
    }

    fclose(file);

    return 0;
}

其中BUFFER_SIZE定义了每次读取的样本数，可以根据需要进行调整。代码首先读取wav文件头，然后按照BUFFER_SIZE批量读取样本数据，计算均值、均方值和方差。注意，计算方差时需要再次从文件头开始读取样本数据。接下来，代码根据自协方差函数的定义计算每个时延的自协方差，最后根据自协方差函数的傅里叶变换定义计算功率谱。

需要注意的是，代码中使用了double类型来存储均值、均方值、方差、自协方差和功率谱，因此可能会有一定的精度误差。如果需要更高的精度，可以使用long double类型或自己实现高精度计算。