Novel robust stability criteria for stochastic hopfield neural networks with time delays

Authors:
Rongni Yang;Huijun Gao;Peng Shi
Affiliations:
Space Control and Inertial Technology Research Center, Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin, China;Fac. of Adv. Tech., Univ. of Glamorgan, Pontypridd, UK and Inst. for Logistics and Supply Chain Management, School of Sci. and Eng., Victoria Univ., Melbourne, Australia and Sch. of Mathematics an ...
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Year:
2009

Citing 13
Cited 23

Robust control of a class of uncertain nonlinear systems

Systems & Control Letters
Global asymptotic stability of Hopfield neural network involving distributed delays

Neural Networks
Robust output feedback control for discrete time-delay uncertain systems

Control and Intelligent Systems
Robust stability of stochastic delayed additive neural networks with Markovian switching

Neural Networks
Robust stability of discrete-time stochastic neural networks with time-varying delays

Neurocomputing
Stochastic Exponential Stability for Markovian Jumping BAM Neural Networks With Time-Varying Delays

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Global Robust Stability of Bidirectional Associative Memory Neural Networks With Multiple Time Delays

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
New Delay-Dependent Exponential Stability for Neural Networks With Time Delay

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Object recognition using multilayer Hopfield neural network

IEEE Transactions on Image Processing
Hopfield neural networks for affine invariant matching

IEEE Transactions on Neural Networks
Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays

IEEE Transactions on Neural Networks
New Delay-Dependent Stability Criteria for Neural Networks With Time-Varying Delay

IEEE Transactions on Neural Networks
A New Criterion of Delay-Dependent Asymptotic Stability for Hopfield Neural Networks With Time Delay

IEEE Transactions on Neural Networks

Neural networks letter: Stability analysis of static recurrent neural networks using delay-partitioning and projection

Neural Networks
Stochastic stability of Markovian jumping Hopfield neural networks with constant and distributed delays

Neurocomputing
Mean Square Exponential Stability of Uncertain Stochastic Hopfield Neural Networks with Interval Time-Varying Delays

ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Robust passivity and passification of stochastic fuzzy time-delay systems

Information Sciences: an International Journal
Neural networks letter: Delay-dependent stability analysis for continuous-time BAM neural networks with Markovian jumping parameters

Neural Networks
On robust stability of stochastic genetic regulatory networks with time delays: a delay fractioning approach

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Global asymptotic stability of stochastic BAM neural networks with distributed delays and reaction-diffusion terms

Journal of Computational and Applied Mathematics
Delay-derivative-dependent stability for delayed neural networks with unbound distributed delay

IEEE Transactions on Neural Networks
Robust state estimation for discrete-time stochastic neural networks with probabilistic measurement delays

Neurocomputing
An LMI approach to stability analysis of reaction-diffusion Cohen-Grossberg neural networks concerning Dirichlet boundary conditions and distributed delays

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
New passivity analysis for neural networks with discrete and distributed delays

IEEE Transactions on Neural Networks
State estimation of recurrent neural networks with time-varying delay: A novel delay partition approach

Neurocomputing
Letter to the editor: Stability analysis on delayed neural networks based on an improved delay-partitioning approach

Journal of Computational and Applied Mathematics
Stability analysis for discrete-time Markovian jump neural networks with mixed time-delays

Expert Systems with Applications: An International Journal
Improved exponential stability criteria for neural networks with time-varying delays

Neurocomputing
Design of a robust neural network-based tracking controller for a class of electrically driven nonholonomic mechanical systems

Information Sciences: an International Journal
Global exponential estimates of delayed stochastic neural networks with Markovian switching

Neural Networks
Robust stability analysis of Markov jump standard genetic regulatory networks with mixed time delays and uncertainties

Neurocomputing
Synchronization of discrete-time neural networks with time delays subject to missing data

Neurocomputing
Letters: Delayed chaotic neural network with annealing controlling for maximum clique problem

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

Neurocomputing
Improved delay-dependent stability criteria for recurrent neural networks with time-varying delays

Neurocomputing
Adaptive neural tracking control for stochastic nonlinear strict-feedback systems with unknown input saturation

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, the problem of asymptotic stability for stochastic Hopfield neural networks (HNNs) with time delays is investigated. New delay-dependent stability criteria are presented by constructing a novel Lyapunov-Krasovskii functional. More-over, the results are further extended to the delayed stochastic HNNs with parameter uncertainties. The main idea is based on the delay partitioning technique, which differs greatly from most existing results and reduces conservatism. Numerical examples are provided to illustrate the effectiveness and less conservativeness of the developed techniques.