public static void compute_fft(double[] data, List <complex> vecList)
{
for (int i = 0; i < (int)FFTLen; ++i)
{
if (i < FrmLen)
{
complex temp = new complex(data[i]);
vecList.Add(temp);
}
else
{
complex temp = new complex(0);
vecList.Add(temp);
}
}
//complex[] List = vecList.ToArray<complex>();
FFT(512, vecList);
}
public static void FFT(uint ulN, List <complex> vecList) //complex[]
{
//得到指数，这个指数实际上指出了计算FFT时内部的循环次数
uint ulPower = 0; //指数
uint ulN1 = ulN - 1; //ulN1=511
while (ulN1 > 0)
{
ulPower++;
ulN1 /= 2;
}
//反序，因为FFT计算后的结果次序不是顺序的，需要反序来调整。可以在FFT实质部分计算之前先调整，也可以在结果
//计算出来后再调整。本程序中是先调整，再计算FFT实质部分
BitArray bsIndex = new BitArray(sizeof(int) * 8);
uint ulIndex; //反转后的序号
uint ulK;
for (ulong p = 0; p < ulN; p++)
{
ulIndex = 0;
ulK = 1;
bsIndex = new BitArray(BitConverter.GetBytes((uint)p));
for (uint j = 0; j < ulPower; j++)
{
ulIndex += bsIndex[(int)(ulPower - j - 1)] ? ulK : 0;
ulK *= 2;
}
if (ulIndex > p) //只有大于时，才调整，否则又调整回去了
{
complex c = vecList[(int)p];
vecList[(int)p] = vecList[(int)ulIndex];
vecList[(int)ulIndex] = c;
}
}
//计算旋转因子
List <complex> vecW = new List <complex>();
for (uint i = 0; i < ulN / 2; i++)
{
vecW.Add(new complex((double)(Math.Cos(2 * i * PI / ulN)), (double)(-1 * Math.Sin(2 * i * PI / ulN))));
}
//计算FFT
uint ulGroupLength = 1; //段的长度
uint ulHalfLength = 0; //段长度的一半
uint ulGroupCount = 0; //段的数量
complex cw; //WH(x)
complex c1; //G(x) + WH(x)
complex c2; //G(x) - WH(x)
complex[] vecW1 = vecW.ToArray <complex>();
for (uint b = 0; b < ulPower; b++)
{
ulHalfLength = ulGroupLength;
ulGroupLength *= 2;
for (int j = 0; j < ulN; j += (int)ulGroupLength)
{
for (int k = 0; k < (int)ulHalfLength; k++)
{
cw = vecW1[k * ulN / ulGroupLength] * vecList[j + k + (int)ulHalfLength];
c1 = vecList[j + k] + cw;
c2 = vecList[j + k] - cw;
vecList[j + k] = c1;
vecList[j + k + (int)ulHalfLength] = c2;
}
}
}
}
