state estimation for discrete-time memristive recurrent neural networks with stochastic time-delays
نویسندگان
چکیده
منابع مشابه
H∞ state estimation for discrete-time memristive recurrent neural networks with stochastic time-delays
Hongjian Liu, Zidong Wang, Bo Shena∗ and Fuad E. Alsaadi School of Information Science and Technology, Donghua University, Shanghai 200051, China; Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB8 3PH, United Kingdom; Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia; School of ...
متن کاملFINITE-TIME PASSIVITY OF DISCRETE-TIME T-S FUZZY NEURAL NETWORKS WITH TIME-VARYING DELAYS
This paper focuses on the problem of finite-time boundedness and finite-time passivity of discrete-time T-S fuzzy neural networks with time-varying delays. A suitable Lyapunov--Krasovskii functional(LKF) is established to derive sufficient condition for finite-time passivity of discrete-time T-S fuzzy neural networks. The dynamical system is transformed into a T-S fuzzy model with uncertain par...
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 کاملStochastic stability of discrete-time uncertain recurrent neural networks with Markovian jumping and time-varying delays
In this paper, the problemof robust exponential stability analysis of uncertain discrete-time recurrent neural networks withMarkovian jumping and time-varying delays is studied. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, a new sufficient criterion is proposed for the global robust exponential stability of discrete-time recurrent neural networks which conta...
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 کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of General Systems
سال: 2016
ISSN: 0308-1079,1563-5104
DOI: 10.1080/03081079.2015.1106731