Projection Method Formulations Of Perceptron And Hopfield Associative Memory Neural Networks

M. Ibrahim Sezan; Henry Stark; Shu-Jen Yeh

doi:10.1117/12.961610

25 October 1989 Projection Method Formulations Of Perceptron And Hopfield Associative Memory Neural Networks

M. Ibrahim Sezan, Henry Stark, Shu-Jen Yeh

Proceedings Volume 1134, Optical Pattern Recognition II; (1989) https://doi.org/10.1117/12.961610
Event: 1989 International Congress on Optical Science and Engineering, 1989, Paris, France

Abstract

Projection method formulations of the perceptron and Hopfield's associative content-addressable memory (ACAM) neural nets are presented. We show that the well-known single-layer perceptron learning algorithm can be formulated using the method of projections onto convex sets (POCS) and that its performance can be improved using this viewpoint. The operation of a modified, binary-valued Hopfield ACAM is shown to be equivalent to the method of generalized projections (GP). A direct extension of the binary-valued ACAM to the continuous-valued case lends itself to a POCS formu-lation.

Citation Download Citation

M. Ibrahim Sezan, Henry Stark, and Shu-Jen Yeh "Projection Method Formulations Of Perceptron And Hopfield Associative Memory Neural Networks", Proc. SPIE 1134, Optical Pattern Recognition II, (25 October 1989); https://doi.org/10.1117/12.961610

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