Stability Criterion of Discrete Hopfield Neural Networks with Weighted Function Matrix and one-Delay

Abstract:

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In this paper, discrete Hopfield neural networks with weight function matrix(WFM) and delay(DHNNWFMD) are presented. And we obtain an important result that if the WFM is a symmetric function matrix(SFM) and delayed function matrix(DFM) is a diagonally dominant function matrix(DDFM), DHNNWFMD will converge to a state in serial mode and if the WFM is a SFM and non-negative definite function matrix(NFM) and DFM is a DDFM, DHNNWFMD will converge to a state in parallel mode. It provides some theory basis for the application of DHNNWFMD.

Info:

Periodical:

Advanced Materials Research (Volumes 271-273)

Edited by:

Junqiao Xiong

Pages:

725-729

DOI:

10.4028/www.scientific.net/AMR.271-273.725

Citation:

H. Y. Zou et al., "Stability Criterion of Discrete Hopfield Neural Networks with Weighted Function Matrix and one-Delay", Advanced Materials Research, Vols. 271-273, pp. 725-729, 2011

Online since:

July 2011

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Price:

$35.00

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