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ETAM by oasisolga is a document available to read on EtoBox.

This document introduces a new approach to associative memory (AM) called error tolerant associative memory (ETAM), which enhances the ability to recover original patterns from noisy inputs. The method improves error tolerance by enlarging the basins of attraction around stored patterns and reducing limit cycles in synchronous operation. The paper discusses the geometric interpretation of the Hopfield network and presents a retraining algorithm to optimize weight and threshold adjustments for better perform

Author

oasisolga

Language

EN