我很难实现使用vDSP的FFT。我理解这个理论,但是我正在寻找一个具体的代码示例。iPhone FFT与Accelerate框架vDSP
我有如下一个wav文件数据:
问题1.我如何把音频数据到FFT?
问题2.如何从FFT中获取输出数据?
问题3.最终目标是检查低频声音。我将如何做到这一点?
-(OSStatus)open:(CFURLRef)inputURL{
OSStatus result = -1;
result = AudioFileOpenURL (inputURL, kAudioFileReadPermission, 0, &mAudioFile);
if (result == noErr) {
//get format info
UInt32 size = sizeof(mASBD);
result = AudioFileGetProperty(mAudioFile, kAudioFilePropertyDataFormat, &size, &mASBD);
UInt32 dataSize = sizeof packetCount;
result = AudioFileGetProperty(mAudioFile, kAudioFilePropertyAudioDataPacketCount, &dataSize, &packetCount);
NSLog([NSString stringWithFormat:@"File Opened, packet Count: %d", packetCount]);
UInt32 packetsRead = packetCount;
UInt32 numBytesRead = -1;
if (packetCount > 0) {
//allocate buffer
audioData = (SInt16*)malloc(2 *packetCount);
//read the packets
result = AudioFileReadPackets (mAudioFile, false, &numBytesRead, NULL, 0, &packetsRead, audioData);
NSLog([NSString stringWithFormat:@"Read %d bytes, %d packets", numBytesRead, packetsRead]);
}
}
return result;
}
FFT下面的代码:
log2n = N;
n = 1 << log2n;
stride = 1;
nOver2 = n/2;
printf("1D real FFT of length log2 (%d) = %d\n\n", n, log2n);
/* Allocate memory for the input operands and check its availability,
* use the vector version to get 16-byte alignment. */
A.realp = (float *) malloc(nOver2 * sizeof(float));
A.imagp = (float *) malloc(nOver2 * sizeof(float));
originalReal = (float *) malloc(n * sizeof(float));
obtainedReal = (float *) malloc(n * sizeof(float));
if (originalReal == NULL || A.realp == NULL || A.imagp == NULL) {
printf("\nmalloc failed to allocate memory for the real FFT"
"section of the sample.\n");
exit(0);
}
/* Generate an input signal in the real domain. */
for (i = 0; i < n; i++)
originalReal[i] = (float) (i + 1);
/* Look at the real signal as an interleaved complex vector by
* casting it. Then call the transformation function vDSP_ctoz to
* get a split complex vector, which for a real signal, divides into
* an even-odd configuration. */
vDSP_ctoz((COMPLEX *) originalReal, 2, &A, 1, nOver2);
/* Set up the required memory for the FFT routines and check its
* availability. */
setupReal = vDSP_create_fftsetup(log2n, FFT_RADIX2);
if (setupReal == NULL) {
printf("\nFFT_Setup failed to allocate enough memory for"
"the real FFT.\n");
exit(0);
}
/* Carry out a Forward and Inverse FFT transform. */
vDSP_fft_zrip(setupReal, &A, stride, log2n, FFT_FORWARD);
vDSP_fft_zrip(setupReal, &A, stride, log2n, FFT_INVERSE);
/* Verify correctness of the results, but first scale it by 2n. */
scale = (float) 1.0/(2 * n);
vDSP_vsmul(A.realp, 1, &scale, A.realp, 1, nOver2);
vDSP_vsmul(A.imagp, 1, &scale, A.imagp, 1, nOver2);
/* The output signal is now in a split real form. Use the function
* vDSP_ztoc to get a split real vector. */
vDSP_ztoc(&A, 1, (COMPLEX *) obtainedReal, 2, nOver2);
/* Check for accuracy by looking at the inverse transform results. */
Compare(originalReal, obtainedReal, n);
感谢
如果您只想检测低频声音,那么使用FFT可能会矫枉过正。你在寻找什么特定的频率/频率,以及多少分辨率? – 2011-06-15 14:05:18
我正在寻找任何包含鼓或贝司声音的频率,以便我可以响应节拍。谢谢 – Simon 2011-06-15 15:16:37
在这种情况下,使用低通滤波器+包络检波器可能会更好 - 实施起来更简单,电池寿命应该更容易,因为它的计算成本更低。 – 2011-06-15 15:19:06