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NEURAL NETWORKS IN ANALOG HARDWARE — DESIGN AND IMPLEMENTATION ISSUES

    https://doi.org/10.1142/S0129065700000041Cited by:20 (Source: Crossref)

    This paper presents a brief review of some analog hardware implementations of neural networks. Several criteria for the classification of general neural networks implementations are discussed and a taxonomy induced by these criteria is presented. The paper also discusses some characteristics of analog implementations as well as some trade-offs and issues identified in the work reviewed. Parameters such as precision, chip area, power consumption, speed and noise susceptibility are discussed in the context of neural implementations. A unified review of various "VLSI friendly" algorithms is also presented. The paper concludes with some conclusions drawn from the analysis of the implementations presented.

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