Robust stability analysis for discrete-time stochastic neural networks systems with time-varying delays

In this paper, the mean square exponential stability is investigated for a class of discrete-time stochastic neural networks with time-varying delays and norm-bounded uncertainties. Based on Lyapunov stability theory and stochastic approaches, delay-dependent criteria are derived to ensure the robust exponential stability in the mean square for the addressed system. Meantime, by using the numerically efficient Matlab LMI Toolbox, a example is presented to show the usefulness of the derived LMI-based stability condition.

[1]  Zidong Wang,et al.  Global Synchronization Control of General Delayed Discrete-Time Networks With Stochastic Coupling and Disturbances , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  Huijun Gao,et al.  New Results on Stability of Discrete-Time Systems With Time-Varying State Delay , 2007, IEEE Transactions on Automatic Control.

[3]  Zidong Wang,et al.  Robust stability of discrete-time stochastic neural networks with time-varying delays , 2008, Neurocomputing.

[4]  Jinde Cao,et al.  Discrete-time bidirectional associative memory neural networks with variable delays , 2005 .

[5]  Zidong Wang,et al.  Global exponential stability of generalized recurrent neural networks with discrete and distributed delays , 2006, Neural Networks.

[6]  Dong Yue,et al.  Robust delay-distribution-dependent stability of discrete-time stochastic neural networks with time-varying delay , 2009, Neurocomputing.

[7]  Zidong Wang,et al.  A delay-dependent LMI approach to dynamics analysis of discrete-time recurrent neural networks with time-varying delays , 2007 .

[8]  Vimal Singh,et al.  New global robust stability results for delayed cellular neural networks based on norm-bounded uncertainties , 2006 .

[9]  Zidong Wang,et al.  State estimation for discrete-time Markovian jumping neural networks with mixed mode-dependent delays ☆ , 2008 .

[10]  Zidong Wang,et al.  Exponential synchronization of stochastic delayed discrete-time complex networks , 2008 .

[11]  Jinde Cao,et al.  Exponential stability analysis of uncertain stochastic neural networks with multiple delays , 2007 .

[12]  Yun Zou,et al.  Improved delay-dependent exponential stability criteria for discrete-time recurrent neural networks with time-varying delays , 2008, Neurocomputing.

[13]  Jun Wang,et al.  Global robust stability of a class of discrete-time interval neural networks , 2006, IEEE Transactions on Circuits and Systems I: Regular Papers.

[14]  Lin Zou,et al.  Periodic solutions for nonautonomous discrete-time neural networks , 2006, Appl. Math. Lett..

[15]  Huijun Gao,et al.  Delay-dependent output-feedback stabilisation of discrete-time systems with time-varying state delay , 2004 .

[16]  Zidong Wang,et al.  Synchronization and State Estimation for Discrete-Time Complex Networks With Distributed Delays , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[17]  Xiaofeng Liao,et al.  LMI-based robust stability analysis of neural networks with time-varying delay , 2005, Neurocomputing.

[18]  Zidong Wang,et al.  Robust stability analysis of generalized neural networks with discrete and distributed time delays , 2006 .

[19]  Piyapong Niamsup,et al.  Robust stability of discrete-time LPD neural networks with time-varying delay , 2009 .

[20]  Zidong Wang,et al.  Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis , 2007 .

[21]  Wu‐Hua Chen,et al.  Mean square exponential stability of uncertain stochastic delayed neural networks , 2008 .