Robust Stochastic Stability Analysis for Uncertain Neutral-Type Delayed Neural Networks Driven by Wiener Process
نویسندگان
چکیده
The robust stochastic stability for a class of uncertain neutral-type delayed neural networks driven by Wiener process is investigated. By utilizing the Lyapunov-Krasovskii functional and inequality technique, some sufficient criteria are presented in terms of linear matrix inequality LMI to ensure the stability of the system. A numerical example is given to illustrate the applicability of the result.
منابع مشابه
Stability Analysis for Uncertain Stochastic Delayed Neural Networks of Neutral-Type with Discrete and Distributed Delays
The paper studies delay-dependent global robust problem for a class of uncertain stochastic delayed neural networks of neutral-type with discrete and distributed delays. Novel stability criteria are obtained in terms of linear matrix inequality (LMI) by employing the LyapunovKrasovskii functional method and using the free-weighting matrices technique. In addition, two examples are given to show...
متن کاملRobust 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 کاملDelay-Range-Dependent Robust Stability for Uncertain Stochastic Neural Networks with Time-Varying Delays
This paper is concerned with the robust stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. By utilizing a Lyapunov-Krasovskii functional and conducting stochastic analysis, the authors show that the addressed neural networks are globally, robustly, and asymptotically stable if a convex optimization problem is feasible. Some stability criteria ...
متن کاملExponential Stability for a Class of Stochastic Reaction-Diffusion Hopfield Neural Networks with Delays
This paper studies the asymptotic behavior for a class of delayed reaction-diffusion Hopfield neural networks driven by finite-dimensional Wiener processes. Some new sufficient conditions are established to guarantee the mean square exponential stability of this system by using Poincaré’s inequality and stochastic analysis technique. The proof of the almost surely exponential stability for this...
متن کاملNew delay dependent robust asymptotic stability for uncertain stochastic recurrent neural networks with multiple time varying delays
This paper is concerned with the stability analysis problem for a class of delayed stochastic recurrent neural networks with both discrete and distributed time-varying delays. By constructing a suitable Lyapunov–Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish sufficient conditions to ensure the global, robust asymptotic stability for the addressed syst...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Applied Mathematics
دوره 2012 شماره
صفحات -
تاریخ انتشار 2012