Neural networks with dynamical threshold

For a neural network with sign-constrained weights weights three types of attractor can affect the dynamics: retrieval, spurious and uniform attractors. The uniform attractors can dominate the dynamics if there is a substancial weight-sign bias. We will show that it is possible to define dynamical thresholds for various learning rules which can eliminate uniform attracting states for any value of the weight-sign bias.

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Year of publication:	1992
Authors:	Campbell, C. ; Wong, K.Y.M.
Published in:	Physica A: Statistical Mechanics and its Applications. - Elsevier, ISSN 0378-4371. - Vol. 185.1992, 1, p. 378-384
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010587323