H∞ state estimation of static neural networks with time-varying delay

Authors:
Qihui Duan;Hongye Su;Zheng-Guang Wu
Affiliations:
National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou, Zhejiang 310027, PR China;National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou, Zhejiang 310027, PR China;National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou, Zhejiang 310027, PR China
Venue:
Neurocomputing
Year:
2012

Citing 14
Cited 2

A comparative study of two modeling approaches in neural networks

Neural Networks
An analysis of exponential stability of delayed neural networks with time varying delays

Neural Networks
Technical communique: Delay-range-dependent control synthesis for time-delay systems with actuator saturation

Automatica (Journal of IFAC)
State estimation for jumping recurrent neural networks with discrete and distributed delays

Neural Networks
Robust H∞ control for a class of nonlinear discrete time-delay stochastic systems with missing measurements

Automatica (Journal of IFAC)
Delay-dependent globally exponential stability criteria for static neural networks: an LMI approach

IEEE Transactions on Circuits and Systems II: Express Briefs
Delay-dependent H∞ and generalized H2 filtering for delayed neural networks

IEEE Transactions on Circuits and Systems Part I: Regular Papers
New Lyapunov-Krasovskii functionals for global asymptotic stability of delayed neural networks

IEEE Transactions on Neural Networks
State estimation for discrete Markovian jumping neural networks with time delay

Neurocomputing
Guaranteed performance state estimation of static neural networks with time-varying delay

Neurocomputing
Technical communique: Reciprocally convex approach to stability of systems with time-varying delays

Automatica (Journal of IFAC)
A reference model approach to stability analysis of neural networks

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Global Asymptotical Stability of Recurrent Neural Networks With Multiple Discrete Delays and Distributed Delays

IEEE Transactions on Neural Networks
Robust State Estimation for Uncertain Neural Networks With Time-Varying Delay

IEEE Transactions on Neural Networks

Stochastic sampled-data control for state estimation of time-varying delayed neural networks

Neural Networks
Delay-dependent H∞ state estimation of neural networks with mixed time-varying delays

Neurocomputing

Quantified Score

Hi-index	0.01

Visualization

Abstract

The problem of H"~ state estimation is investigated for static neural networks with time-varying delays. Both delay-dependent and delay-independent criteria are presented such that the resulting error system is globally asymptotically stable with a guaranteed H"~ performance. The desired estimator matrix gain can be characterized in terms of the solution to linear matrix inequalities (LMIs). Numerical examples are addressed to show the effectiveness of the proposed design methods.