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Neural Computing and Applications

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11-01-2016 | Original Article

Global exponential convergence of non-autonomous SICNNs with multi-proportional delays

Author: Bingwen Liu

Published in: Neural Computing and Applications | Issue 8/2017

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Abstract

We give a detailed analysis on convergence for a class of non-autonomous shunting inhibitory cellular neural networks involving multi-proportional delays. By employing the differential inequality techniques, we establish a novel result to ensure that all solutions of the addressed system converge exponentially to zero vector. Moreover, numerical simulations supporting our theoretical results are also included.

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Title: Global exponential convergence of non-autonomous SICNNs with multi-proportional delays
Author: Bingwen Liu
Publication date: 11-01-2016
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 8/2017
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-015-2165-8

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