TY - JOUR
T1 - Design of delay-dependent state estimator for discrete-time recurrent neural networks with interval discrete and infinite-distributed time-varying delays
AU - Liao, Chin Wen
AU - Lu, Chien Yu
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011/6
Y1 - 2011/6
N2 - The state estimation problem for discrete-time recurrent neural networks with both interval discrete and infinite-distributed time-varying delays is studied in this paper, where interval discrete time-varying delay is in a given range. The activation functions are assumed to be globally Lipschitz continuous. A delay-dependent condition for the existence of state estimators is proposed based on new bounding techniques. Via solutions to certain linear matrix inequalities, general full-order state estimators are designed that ensure globally asymptotic stability. The significant feature is that no inequality is needed for seeking upper bounds for the inner product between two vectors, which can reduce the conservatism of the criterion by employing the new bounding techniques. Two illustrative examples are given to demonstrate the effectiveness and applicability of the proposed approach.
AB - The state estimation problem for discrete-time recurrent neural networks with both interval discrete and infinite-distributed time-varying delays is studied in this paper, where interval discrete time-varying delay is in a given range. The activation functions are assumed to be globally Lipschitz continuous. A delay-dependent condition for the existence of state estimators is proposed based on new bounding techniques. Via solutions to certain linear matrix inequalities, general full-order state estimators are designed that ensure globally asymptotic stability. The significant feature is that no inequality is needed for seeking upper bounds for the inner product between two vectors, which can reduce the conservatism of the criterion by employing the new bounding techniques. Two illustrative examples are given to demonstrate the effectiveness and applicability of the proposed approach.
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U2 - 10.1007/s11571-010-9135-8
DO - 10.1007/s11571-010-9135-8
M3 - Article
C2 - 22654986
AN - SCOPUS:80051790973
VL - 5
SP - 133
EP - 143
JO - Cognitive Neurodynamics
JF - Cognitive Neurodynamics
SN - 1871-4080
IS - 2
ER -