Robust state estimation for discrete-time BAM neural networks with time-varying delay

被引：35

作者：

Arunkumar, A. ^{[1
]}

Sakthivel, R. ^{[2
,3
]}

Mathiyalagan, K. ^{[1
]}

Anthoni, S. Marshal ^{[1
]}

机构：

[1] Anna Univ, Reg Ctr, Dept Math, Coimbatore 641047, Tamil Nadu, India

[2] Sungkyunkwan Univ, Dept Math, Suwon 440746, South Korea

[3] Sri Ramakrishna Inst Technol, Dept Math, Coimbatore 641010, Tamil Nadu, India

来源：

NEUROCOMPUTING | 2014年 / 131卷

关键词：

Discrete-time; BAM neural networks; State estimation; Linear matrix inequality; Lyapunov-Krasovskii functional; NEUTRAL-TYPE; STABILITY; DESIGN;

D O I：

10.1016/j.neucom.2013.10.027

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper is concerned with the robust delay-dependent state estimation problem for a class of discrete-time Bidirectional Associative Memory (BAM) neural networks with time-varying delays. By using the Lyapunov-Krasovskii functional together with linear matrix inequality (LMI) approach, a new set of sufficient conditions are derived for the existence of state estimator such that the error state system is asymptotically stable. More precisely, an LMI-based state estimator and delay-dependent stability criterion for delayed BAM neural networks are developed. The conditions are established in terms of LMIs which can be solved by the MATLAB LMI toolbox. It should be mentioned that all the sufficient conditions are dependent on the upper and lower bounds' of the delays. Also, the desired estimator unknown gain matrix is determined in terms of the solution to these LMIs. Finally, numerical examples with simulation results are given to illustrate the effectiveness and applicability of the obtained results. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：171 / 178

页数：8

共 25 条

[1] State estimation for fuzzy cellular neural networks with time delay in the leakage term, discrete and unbounded distributed delays [J].

Balasubramaniam, P. ;

Kalpana, M. ;

Rakkiyappan, R. .

COMPUTERS & MATHEMATICS WITH APPLICATIONS, 2011, 62 (10) :3959-3972

[2] Delay-dependent robust exponential state estimation of Markovian jumping fuzzy Hopfield neural networks with mixed random time-varying delays [J].

Balasubramaniam, P. ;

Vembarasan, V. ;

Rakkiyappan, R. .

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2011, 16 (04) :2109-2129

[3] Robust state estimation for uncertain stochastic bidirectional associative memory networks with time-varying delays [J].

Bao, Haibo ;

Cao, Jinde .

PHYSICA SCRIPTA, 2011, 83 (06)

[4] Delay-distribution-dependent state estimation for discrete-time stochastic neural networks with random delay [J].

Bao, Haibo ;

Cao, Jinde .

NEURAL NETWORKS, 2011, 24 (01) :19-28

[5] Stochastic state estimation for neural networks with distributed delays and Markovian jump [J].

Chen, Yun ;

Zheng, Wei Xing .

NEURAL NETWORKS, 2012, 25 :14-20

[6] State estimation of recurrent neural networks with time-varying delay: A novel delay partition approach [J].

Huang, He ;

Feng, Geng .

NEUROCOMPUTING, 2011, 74 (05) :792-796

[7] BIDIRECTIONAL ASSOCIATIVE MEMORIES [J].

KOSKO, B .

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1988, 18 (01) :49-60

[8] State Estimation for Coupled Uncertain Stochastic Networks With Missing Measurements and Time-Varying Delays: The Discrete-Time Case [J].

Liang, Jinling ;

Wang, Zidong ;

Liu, Xiaohui .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2009, 20 (05) :781-793

[9] State estimation for discrete-time Markovian jumping neural networks with mixed mode-dependent delays [J].

Liu, Yurong ;

Wang, Zidong ;

Liu, Xiaohui .

PHYSICS LETTERS A, 2008, 372 (48) :7147-7155

[10] Design of state estimator for uncertain neural networks via the integral-inequality method [J].

Lou, Xuyang ;

Cui, Baotong .

NONLINEAR DYNAMICS, 2008, 53 (03) :223-235

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