Further results on dissipativity analysis of neural networks with time-varying delay and randomly occurring uncertainties

Title
Further results on dissipativity analysis of neural networks with time-varying delay and randomly occurring uncertainties
Author(s)
박주현H.B. Zeng[H.B. Zeng]J.W. Xia[J.W. Xia]
Keywords
GLOBAL ASYMPTOTIC STABILITY; H-INFINITY CONTROL; EXPONENTIAL STABILITY; DISTRIBUTED DELAYS; DISCRETE; SYSTEMS; PARAMETERS; CRITERIA; MATRIX
Issue Date
201501
Publisher
SPRINGER
Citation
NONLINEAR DYNAMICS, v.79, no.1, pp.83 - 91
Abstract
In this paper, the problem of robust dissipativity is investigated for neural networks with both time-varying delay and randomly occurring uncertainties. The randomly occurring uncertainties are assumed to obey mutually uncorrelated Bernoulli-distributed white noise sequences. By constructing a new Lyapunov-Krasovskii functional, some improved delay-dependent dissipativity conditions are derived based on two integral inequalities, which are formulated in terms of linear matrix inequality. Furthermore, some information of activation function ignored in previous works has been taken into account in the resulting condition. The effectiveness and the improvement of the proposed approach are demonstrated by two illustrating numerical examples.
URI
http://hdl.handle.net/YU.REPOSITORY/33688http://dx.doi.org/10.1007/s11071-014-1646-0
ISSN
0924-090X
Appears in Collections:
공과대학 > 전기공학과 > Articles
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