Publication Type

Journal Article

Version

publishedVersion

Publication Date

4-2015

Abstract

As can be represented by neurons and their synaptic connections, attractor networks are widely believed to underlie biological memory systems and have been used extensively in recent years to model the storage and retrieval process of memory. In this paper, we propose a new energy function, which is nonnegative and attains zero values only at the desired memory patterns. An attractor network is designed based on the proposed energy function. It is shown that the desired memory patterns are stored as the stable equilibrium points of the attractor network. To retrieve a memory pattern, an initial stimulus input is presented to the network, and its states converge to one of stable equilibrium points. Consequently, the existence of the spurious points, that is, local maxima, saddle points, or other local minima which are undesired memory patterns, can be avoided. The simulation results show the effectiveness of the proposed method.

Discipline

Databases and Information Systems | OS and Networks

Research Areas

Data Science and Engineering

Publication

Computational Intelligence and Neuroscience

First Page

1

Last Page

7

ISSN

1687-5265

Identifier

10.1155/2015/191745

Publisher

Hindawi

Additional URL

https://doi.org/10.1155/2015/191745

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