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November 14, 2016 03:01
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DFT Implementations, including FFT
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private static Complex[] DFTDirectComputation(Complex[] input) | |
{ | |
int N = input.Length; | |
Complex[] output = new Complex[input.Length]; | |
for (int k = 0; k < input.Length; k++) | |
{ | |
var sum = new Complex(); | |
for (int n = 0; n < input.Length; n++) | |
{ | |
sum += input[n] * WFunction(N, k * n); | |
} | |
output[k] = sum; | |
} | |
return output; | |
} | |
private static Complex[] DFTSlightlyFaster(Complex[] input) | |
{ | |
int N = input.Length; | |
Complex[] output = new Complex[input.Length]; | |
for (int k = 0; k < input.Length; k++) | |
{ | |
var evenSum = new Complex(); | |
var oddSum = new Complex(); | |
for (int m = 0; m < N / 2; m++) | |
{ | |
evenSum += input[2 * m] * WFunction(N / 2, k * m); | |
oddSum += input[2 * m + 1] * WFunction(N / 2, k * m); | |
} | |
oddSum = oddSum * WFunction(N, k); | |
output[k] = evenSum + oddSum; | |
} | |
return output; | |
} | |
private static Complex[] DFTUsingFFT(Complex[] input) | |
{ | |
int N = input.Length; | |
Complex[] output = new Complex[input.Length]; | |
if (input.Length == 1) | |
{ | |
output[0] = input[0]; | |
} | |
else | |
{ | |
Complex[] evenPoints = input.Where((c, i) => i % 2 == 0).ToArray(); | |
Complex[] oddPoints = input.Where((c, i) => i % 2 == 1).ToArray(); | |
Complex[] evenDft = DFTUsingFFT(evenPoints); | |
Complex[] oddDft = DFTUsingFFT(oddPoints); | |
for (int k = 0; k < N / 2; k++) | |
{ | |
output[k] = evenDft[k] + WFunction(N, k) * oddDft[k]; | |
output[k + N / 2] = evenDft[k] - WFunction(N, k) * oddDft[k]; | |
} | |
} | |
return output; | |
} | |
private static Complex WFunction( | |
int N, | |
int expOfW | |
) | |
{ | |
return new Complex(Math.Cos((2 * Math.PI / N) * expOfW), -Math.Sin((2 * Math.PI / N) * expOfW)); | |
} |
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