Stability of stochastic delay neural networks
نویسندگان
چکیده
The authors in their papers (Liao and Mao, Stochast. Anal. Appl. 14 (2) (1996a) 165–185; Neural, Parallel Sci. Comput. 4 (2) (1996b) 205–244) initiated the study of stability and instability of stochastic neural networks and this paper is the continuation of their research in this area. The main aim of this paper is to discuss almost sure exponential stability for a stochastic delay neural network dxðtÞ 1⁄4 1⁄2 BxðtÞ þ AgðxtðtÞÞ dtþ sðxðtÞ; gðxtðtÞ; tÞ dwðtÞ. The techniques used in this paper are different from those in their earlier papers. Especially, the nonnegative semimartingale convergence theorem will play an important role in this paper. Several examples are also given for illustration. # 2001 The Franklin Institute. Published by Elsevier Science Ltd. All rights reserved.
منابع مشابه
Robust stability of stochastic fuzzy impulsive recurrent neural networks with\ time-varying delays
In this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the Takagi-Sugeno (T-S) fuzzy models is considered. A novel Linear Matrix Inequality (LMI)-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...
متن کاملRobust stability of fuzzy Markov type Cohen-Grossberg neural networks by delay decomposition approach
In this paper, we investigate the delay-dependent robust stability of fuzzy Cohen-Grossberg neural networks with Markovian jumping parameter and mixed time varying delays by delay decomposition method. A new Lyapunov-Krasovskii functional (LKF) is constructed by nonuniformly dividing discrete delay interval into multiple subinterval, and choosing proper functionals with different weighting matr...
متن کاملDelay-dependent Stability for Uncertain Stochastic Bam Neural Networks with Time-varying Delay
This paper deals with the problem of delay-dependent asymptotically stability for stochastic bidirectional associative memory neural networks with time-varying structured uncertainties and time-varying delays. The parameter uncertainties are assumed to be norm bounded. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, new delay-dependent stability criteria ...
متن کاملDecentralized Adaptive Control of Large-Scale Non-affine Nonlinear Time-Delay Systems Using Neural Networks
In this paper, a decentralized adaptive neural controller is proposed for a class of large-scale nonlinear systems with unknown nonlinear, non-affine subsystems and unknown nonlinear time-delay interconnections. The stability of the closed loop system is guaranteed through Lyapunov-Krasovskii stability analysis. Simulation results are provided to show the effectiveness of the proposed approache...
متن کاملNovel Delay-Dependent Stability Criteria for Uncertain Discrete-Time Stochastic Neural Networks with Time-Varying Delays
This paper investigates the problem of exponential stability for a class of uncertain discrete-time stochastic neural network with time-varying delays. By constructing a suitable LyapunovKrasovskii functional, combining the stochastic stability theory, the free-weighting matrix method, a delay-dependent exponential stability criteria is obtained in term of LMIs. Compared with some previous resu...
متن کاملStability Analysis for Stochastic Markovian Jumping Neural Networks with Leakage Delay
Abstract: The stability problem for a class of stochastic neural networks with Markovian jump parameters and leakage delay is addressed in this study. The sufficient condition to ensure an exponentially stable stochastic neural networks system is presented and proven with Lyapunov functional theory, stochastic stability technique and linear matrix inequality method. The effect of leakage delay ...
متن کامل