supported by Natural Science Foundation of Jiangsu Province of China(No.BK2007016);Scientific Research and Development Program of the Higher Education Institutions of Shandong Province of China(No.J09LG58)
This paper investigates the problem of robust exponential stability for neutral systems with time-varying delays and nonlinear perturbations. Based on a novel Lyapunov functional approach and linear matrix inequality ...
Project supported by the National Natural Science Foundation of China (Grant No.60674026);the Jiangsu Provincial Natural Science Foundation of China (Grant No.BK2007016)
In this paper, we have improved delay-dependent stability criteria for recurrent neural networks with a delay varying over a range and Markovian jumping parameters. The criteria improve over some previous ones in that...
Project supported by the Natural Science Foundation of Jiangsu Province,China (Grant No. BK2007016)
In this paper, the problem of generalised synchronisation of two different chaotic systems is investigated. Some less conservative conditions are derived using linear matrix inequality other than existing results. Fur...
Project supported by the National Natural Science Foundation of China (Grant No 60674026);the Natural Science Foundation of Jiangsu Province of China (Grant No BK2007016)
This paper studies delay-dependent asymptotical stability problems for the neural system with time-varying delay. By dividing the whole interval into multiple segments such that each segment has a different Lyapunov m...
Project supported by National Natural Science Foundation of China (Grant No 60674026);the Jiangsu Provincial Natural Science Foundation of China (Grant No BK2007016);Program for Innovative Research Team of Jiangnan University,China
This paper investigates the global synchronization in an array of linearly coupled neural networks with constant and delayed coupling. By a simple combination of adaptive control and linear feedback with the updated l...
Project supported by the National Natural Science Foundation of China (Grant No 60674026);the Key Project of Chinese Ministry of Education (Grant No 107058);the Jiangsu Provincial Natural Science Foundation of China (Grant No BK2007016);the Jiangsu Provincial Program for Postgraduate Scientific Innovative Research of Jiangnan University (Grant No CX07B_116z)and PIRT Jiangnan
This paper focuses on sliding mode control problems for a class of nonlinear neutral systems with time-varying delays. An integral sliding surface is firstly constructed. Then it finds a useful criteria to guarantee t...
This work was supported by National Natural Science Foundation of China (No. 60674026);Key Project of Chinese Ministry of Edu- cation (No. 107058);Jiangsu Provincial Natural Science Foundation of China (No. BK2007016)
A new definition of dissipativity for neural networks is presented in this paper. By constructing proper Lyapunov functionals and using some analytic techniques, sufficient conditions are given to ensure the dissipati...
supported by National Natural Science Foundation of China (Grant No 60674026);the Jiangsu Provincial Natural Science Foundation of China (Grant No BK2007016);Program for Innovative Research Team of Jiangnan University of China
This paper studies the global exponential stability of competitive neural networks with different time scales and time-varying delays. By using the method of the proper Lyapunov functions and inequality technique, som...
Project supported by the National Natural Science Foundation of China (Grant No 60674026);the Key Project of Chinese Ministryof Education (Grant No 107058);the Jiangsu Provincial Natural Science Foundation of China (Grant No BK2007016);the Jiangsu Provincial Program for Postgraduate Scientific Innovative Research of Jiangnan University (Grant No CX07B 116z)
In this paper, we focus on the robust adaptive synchronization between two coupled chaotic neural networks with all the parameters unknown and time-varying delay. In order to increase the robustness of the two coupled...