Abstract
The availability of effective and low-cost neural hardware opens the gate towards applications of neural networks which can compete with other techniques. This paper describes the design problems of silicon neural architectures, and analyzes the various implementations choices. Emphasys is on methodology and principles. Pointers to descriptions of specific neural circuits are provided.
Cite
CITATION STYLE
Del Corso, D. (1993). Hardware implementations of artificial neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 686, pp. 405–419). Springer Verlag. https://doi.org/10.1007/3-540-56798-4_181
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