Fourier analysis of the generalized CMAC neural network.

Artés-Rodriguez, Antonio; Figueiras-Vidal, Anibal R.; González-Serrano, Francisco J. · Neural Netw · 1998

basic_science · Level V

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Abstract

THE CEREBELLAR MODEL ARTICULATION CONTROLLER (CMAC) IS A SIMPLE AND FAST NEURAL NETWORK: these characteristics have extended its successful applications, while the analysis of its representation capabilities, as for many other neural networks, did not follow a similar development.IN THIS ARTICLE WE DISCOVER THE CLOSE PARALLELISM BETWEEN THE REPRESENTATION OF A FUNCTION BY A GENERALIZED CMAC (GCMAC) AND NYQUIST SAMPLING THEORY: discussing the role of different parameters and components of the network according to this similarity. The consideration of a representative example shows how the parallelism can be used to design a GCMAC adapted to its particular application.