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10.8: Numerical Accuracy in FFTs

  • Page ID
    2800
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    An important consideration in the implementation of any practical numerical algorithm is numerical accuracy: how quickly do floating-point roundoff errors accumulate in the course of the computation? Fortunately, FFT algorithms for the most part have remarkably good accuracy characteristics. In particular, for a DFT of length \(n\) computed by a Cooley-Tukey algorithm with finite-precision floating-point arithmetic, the worst-case error growth is O(logn)O(logn)" role="presentation" style="position:relative;" tabindex="0">


    This page titled 10.8: Numerical Accuracy in FFTs is shared under a CC BY license and was authored, remixed, and/or curated by C. Sidney Burrus.

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