Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19065
Title: Stability of discrete Hopfield neural networks with time-delay
Authors: Qiu, SS
Tsang, ECC
Yeung, DS
Keywords: Hopfield neural nets
Convergence
Delays
Discrete systems
Stability
Issue Date: 2000
Publisher: IEEE
Source: 2000 IEEE International Conference on Systems, Man, and Cybernetics, October 2000, Nashville, TN, v. 4, p. 2545-2550 How to cite?
Abstract: It is well-known that discrete Hopfield neural networks (DHNNs) without delay converge to a stable state. Due to this property, DHNNs without delay have wide potential applications to many fields, such as associative memory devices and combinatorial optimization. A DHNN with delay, which can deal with temporal information, is a generalization of a DHNN without delay. This paper investigates the convergence theorems of DHNNs with delay, based on new updating modes. A new bivariate energy function is constructed which represents the relationships between application problems and DHNNs with delay. It is proved that DHNNs with delay converge to a stable state. These results extend the existing results corresponding to DHNNs without delay. We also relate the maximum of this energy function to a stable state of DHNNs with delay. Furthermore, we describe algorithms for DHNNs with delay in detail
URI: http://hdl.handle.net/10397/19065
ISBN: 0-7803-6583-6
ISSN: 1062-922X
DOI: 10.1109/ICSMC.2000.884376
Appears in Collections:Conference Paper

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