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Exponential stability preservation in discrete-time analogues of artificial neural networks with distributed delays

✍ Scribed by Sannay Mohamad

Publisher: Elsevier Science
Year: 2008
Tongue: English
Weight: 280 KB
Volume: 215
Category: Article
ISSN: 0377-0427
DOI: 10.1016/j.cam.2007.04.009

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✦ Synopsis

This paper demonstrates that there is a discrete-time analogue which does not require any restriction on the size of the time-step in order to preserve the exponential stability of an artificial neural network with distributed delays. The analysis exploits an appropriate Lyapunov sequence and a discrete-time system of Halanay inequalities, and also either a Young inequality or a geometric-arithmetic mean inequality, to derive several sufficient conditions on the network parameters for the exponential stability of the analogue. The sufficiency conditions are independent of the time-step, and they correspond to those that establish the exponential stability of the continuous-time network.

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