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Cooley–Tukey FFT vs Conventional DFT Algorithm


Cooley–Tukey FFT vs Conventional FFT Algorithm

Understanding the difference between the Cooley–Tukey Fast Fourier Transform and the conventional FFT/DFT computation.

1. Conventional FFT Algorithm

The conventional FFT algorithm usually refers to the direct computation of the Discrete Fourier Transform (DFT). The DFT of a sequence of length \(N\) is:

\[
X[k] = \sum_{n=0}^{N-1} x[n] e^{-j 2\pi nk / N}, \quad k = 0,1,\dots,N-1
\]
    

Direct DFT computation requires O(N²) operations (multiplications and additions) and can be slow for large sequences.

2. Cooley–Tukey FFT Algorithm

The Cooley–Tukey algorithm is a widely used FFT method based on divide-and-conquer. It splits a DFT of size \(N\) into smaller DFTs, which reduces computation to O(N log N).

For a sequence of length \(N\) (ideally a power of 2), the algorithm splits into even and odd indices:

\[
X[k] = \sum_{n=0}^{N/2-1} x[2n] e^{-j 2\pi k (2n)/N} + \sum_{n=0}^{N/2-1} x[2n+1] e^{-j 2\pi k (2n+1)/N}
\]
    

3. Key Differences

Feature Conventional DFT / FFT Cooley–Tukey FFT
Complexity O(N²) O(N log N)
Method Direct sum over all points Divide-and-conquer, split into smaller DFTs
Optimal N Any N Most efficient when N = 2^m
Memory / Implementation Simple, direct Bit-reversal and twiddle factors required
Speed Slower for large N Much faster, widely used in practice

4. Summary

Conventional FFT is the brute-force, direct computation of DFT and is slower for large sequences.
Cooley–Tukey FFT uses divide-and-conquer, reducing computational complexity and making FFT practical for large datasets.

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