Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33935
Title: Exponential stability of numerical solutions to stochastic delay Hopfield neural networks
Authors: Li, R
Pang, WK
Leung, PK 
Keywords: Euler method
GMS-stability
MS-stability
Semi-implicit Euler method
Stochastic delay Hopfield neural networks
Issue Date: 2010
Publisher: Elsevier
Source: Neurocomputing, 2010, v. 73, no. 4-6, p. 920-926 How to cite?
Journal: Neurocomputing 
Abstract: The main aim of this paper is to investigate the exponential stability of the Euler method and the semi-implicit Euler method for stochastic delay Hopfield neural networks. The definition of MS-stability and GMS-stability of these two numerical methods is introduced. Under the conditions which guarantee the stability of the analytical solution, the Euler scheme is proved to be MS-stable and the semi-implicit scheme is to be MS-stable and GMS-stable. An example is given for illustration.
URI: http://hdl.handle.net/10397/33935
ISSN: 0925-2312
EISSN: 1872-8286
DOI: 10.1016/j.neucom.2009.09.007
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