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Implementation of Spectral Transformations in the Class of Fast Neural Networks

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Abstract

In the paper, the use of neural networks for the implementation of fast algorithms of spectral transformations is discussed. It is shown that the fast algorithms are particular cases of fast neural networks (FNNs). Methods for parametric tuning FNNs to a given system of basis functions are suggested. Neural network implementations of the fast Walsh and wavelet transformations and the fast Fourier, Vilenkin–Christiansen, and Haar transforms are constructed. The discussions are illustrated by examples.

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  1. St. Petersburg State University of Electrical Engineering, St. Petersburg, Russia

    A. Yu. Dorogov

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  1. A. Yu. Dorogov
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Dorogov, A.Y. Implementation of Spectral Transformations in the Class of Fast Neural Networks. Programming and Computer Software 29, 187–198 (2003). https://doi.org/10.1023/A:1024966508452

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