Difference between revisions of "Fast Fourier Transform"

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(<math>-ify the expressions)
m (... that's not true. Most FFT algorithms are power 2 based, however there can be mixed radix implementations ;-D)
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Fast Fourier Transform is an efficient algorithm for calculating the discrete fourier transform ([[DFT]]). Reduces the execution time by hundreds in some cases. Whereas [[DFT]] takes an order of <math>O(n^2)\,</math> computations, FFT takes an order of <math>O(n\,\log\,n)</math>, and is definitely the preferred algorithm to used in all applications. The disadvantage of the FFT is that the number of samples must be exactly a power of 2.
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Fast Fourier Transform is an efficient algorithm for calculating the discrete fourier transform ([[DFT]]). Reduces the execution time by hundreds in some cases. Whereas [[DFT]] takes an order of <math>O(n^2)\,</math> computations, FFT takes an order of <math>O(n\,\log\,n)</math>, and is definitely the preferred algorithm to used in all applications. The FFT in most implementations consistent of samples that are exactly a power of 2.
  
  
[[Category:Technical]]
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[[Category:Algorithms]]

Revision as of 22:22, 2 September 2006

Fast Fourier Transform is an efficient algorithm for calculating the discrete fourier transform (DFT). Reduces the execution time by hundreds in some cases. Whereas DFT takes an order of O(n^2)\, computations, FFT takes an order of O(n\,\log\,n), and is definitely the preferred algorithm to used in all applications. The FFT in most implementations consistent of samples that are exactly a power of 2.