FFT音频输入 [英] FFT audio input

问题描述

我想申请FFT上记录AudioRecorder并保存为WAV文件的信号。我现在用的FFT有一个复杂的[]输入参数。我很困惑，有没有从字节COMLEX分割的实部将通过32768，并只需添加0的虚部转换，并留下一个字节之间的区别是什么？

编辑：

 公共复杂[] convertToComplex（byte []的文件）
{


    INT大小= file.length;
    双[]×=新的双[尺寸]
    复[]数据=新的复杂【尺寸】;
    的for（int i = 0; I＆LT;大小;我++）
    {
        X [i] =文件[I] /32768.0;
        数据[I] =新复合物（X [I]中，0）;
        // Log.d（标签，指数之+ I +：+数据[I]）;
    }
    返回的数据;
}
 

解决方案

如果您正在使用音频位深度为16位（每个样品有16位），然后每个字节只会有一半sample.What的你需要做的是投你的字节到16位采样，然后通过32768除以得到的数字（这是最小号的幅度的2的补16位的数字可以存储即2 ^ 15），以获得实际的音频采样这是一种介于-1和1。你数量将随后通过它的虚分量设置为0这个数转换为复数。

一个小的C＃示例可以看出以下（指示code）：

 字节[] myAudioBytes = readAudio（）;
    INT的numBytes = myAudioBytes.Length;

    VAR myAudioSamples =名单，其中，短期＆GT;（）;

    的for（int i = 0; I＆LT;的numBytes; I = I + 2）
    {
      //强制转换为16位音频，然后加样
       短样本=（短）（（myAudioBytes [1]  - ;＆所述; 8 | myAudioBytes [I + 1]）/ 32768）;
       myAudioSamples.Add（样品）;
    }

    //改变真实音频到复杂的音频

    复[] complexAudio =新的复杂[myAudioSamples.Length]

    INT I = 0;
    的foreach（在myAudioSamples短样品）
       complexAudio [我+ +] =新的复杂（）{实=样品，虚= 0};

   //现在您可以继续让你的音频的FFT这里
 

望code具有引导你，你应该如何处理您的声音。

I want to apply FFT on a signal recorded by AudioRecorder and saved to a wav file. the FFT i am using has a Complex[] input parameter. I am confused, is there a difference between converting from bytes to comlex dividing by 32768, and converting by just adding 0 to the imaginary part and leaving the real part as a byte?

Edit:

public Complex[] convertToComplex(byte[] file)
{


    int size= file.length;
    double[]x=new double[size];
    Complex[]data= new Complex[size];
    for(int i=0;i<size;i++)
    {
        x[i]=file[i]/32768.0;
        data[i]=new Complex(x[i],0);
        //  Log.d("tag", "indice"+i+":"+data[i]);
    }
    return data;
}

解决方案

If you are working with audio with a bit depth of 16 bits (each sample has 16 bits), then each byte will only have half of a sample.What you need to do is cast your bytes to 16 bit samples then divide the resulting number by 32768 (This is the magnitude of the smallest number a 2's complement 16 bit number can store i.e 2^15) to get the actual audio sample which is a number between -1 and 1.You will then convert this number to a complex number by setting it's imaginary component to 0.

A small C# sample can be seen below (indicative code):

    byte[] myAudioBytes = readAudio();
    int numBytes = myAudioBytes.Length;

    var myAudioSamples = List<short>();

    for( int i = 0; i < numBytes; i = i + 2)
    {
      //Cast to 16 bit audio and then add sample
       short sample = (short) ((myAudioBytes[i] << 8 | myAudioBytes[i + 1]) / 32768 ); 
       myAudioSamples.Add(sample);
    }

    //Change real audio to Complex audio

    Complex[] complexAudio = new Complex[myAudioSamples.Length];

    int i = 0;
    foreach(short sample in myAudioSamples)
       complexAudio[i++] = new Complex(){ Real = sample, Imaginary = 0 };

   //Now you can proceed to getting the FFT of your Audio here

Hope the code has guided you on how you should handle your audio.

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