Robust passivity analysis of neural networks with discrete and distributed delays

Title
Robust passivity analysis of neural networks with discrete and distributed delays
Author(s)
박주현H.B. Zeng[H.B. Zeng]H. Shen[H. Shen]
Keywords
TIME-VARYING DELAYS; GLOBAL EXPONENTIAL STABILITY; DEPENDENT STABILITY; ASYMPTOTIC STABILITY; CRITERIA; SYSTEMS; PARAMETERS
Issue Date
201502
Publisher
ELSEVIER SCIENCE BV
Citation
NEUROCOMPUTING, v.149, pp.1092 - 1097
Abstract
This paper focuses on the problem of passivity of neural networks in the presence of discrete and distributed delay. By constructing an augmented Lyapunov functional and combining a new integral inequality with the reciprocally convex approach to estimate the derivative of the Lyapunov-Krasovskii functional; sufficient conditions are established to ensure the passivity of the considered neural networks, in which some useful information on the neuron activation function ignored in the existing literature is taken into account. Three numerical examples are provided to demonstrate the effectiveness and the merits of the proposed method. (C) 2014 Elsevier B.V. All rights reserved.
URI
http://hdl.handle.net/YU.REPOSITORY/33433http://dx.doi.org/10.1016/j.neucom.2014.07.024
ISSN
0925-2312
Appears in Collections:
공과대학 > 전기공학과 > Articles
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