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Max–min fuzzy Hopfield neural networks and an efficient learning algorithm

✍ Scribed by Puyin Liu

Publisher: Elsevier Science
Year: 2000
Tongue: English
Weight: 117 KB
Volume: 112
Category: Article
ISSN: 0165-0114
DOI: 10.1016/s0165-0114(98)00091-8

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✦ Synopsis

We set up a dynamical fuzzy neural network system, i.e. the so-called max-min fuzzy Hopÿeld network in the paper, and prove the Lyapunov stability of the equilibrium points (attractor) of the system. Also, we discuss the uniform stability of the system and show some su cient conditions, with which the given fuzzy pattern is the attractor of the system. Moreover, we obtain a nontrivially attractive basin of the attractor. Therefore, our models have good fault-tolerance. With an analytic method, we design an e cient learning algorithm for connected weights of the networks. Finally, simulation examples demonstrate our conclusions.

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