title: Fourier analysis of the generalized CMAC neural network.
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.
authors.affiliation: DSSR-ETSI Telecomunicación, UPM. Ciudad Universitaria, Madrid, Spain
authors.forename: Antonio
authors.initials: A
authors.lastname: Artés-Rodriguez
authors.forename: Anibal R.
authors.initials: AR
authors.lastname: Figueiras-Vidal
authors.forename: Francisco J.
authors.initials: FJ
authors.lastname: González-Serrano