Exponential Stability of Periodic Solutions for Inertial Cohen-grossberg-type Neural Networks
نویسندگان
چکیده
In this paper, the exponential stability of periodic solutions for inertial Cohen-Grossberg-type neural networks are investigated. First, by properly chosen variable substitution the system is transformed to first order differential equation. Second, some sufficient conditions which can ensure the existence and exponential stability of periodic solutions for the system are obtained by using constructing suitable Lyapunov function and differential mean value theorem, applying the analysis method and inequality technique. Finally, two examples are given to illustrate the effectiveness of the results.
منابع مشابه
Exponential stability of periodic solutions for inertial Cohen-Grossberg-type BAM neural networks with time delays
Abstract: The paper is concerned with the existence and global exponential stability of periodic solutions for inertial Cohen-Grossberg-type BAM neural networks with time delays. With variable transformation the system is transformed to first order differential equations. Some new sufficient conditions ensuring the existence and global exponential stability of periodic solutions for the system ...
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 کاملExponential Stability of Periodic Solutions for Cohen-Grossberg Neural Networks with Continuously Distributed Delays
A class of Cohen-Grossberg neural networks with distributed delays are considered. By using the coincidence degree theorem and differential inequality techniques, sufficient conditions for the existence and exponential stability of the periodic solutions are established, Without assuming the boundedness, monotonicity, and differentiability of activation functions and any symmetry of interconnec...
متن کاملStability analysis of periodic solutions for stochastic reaction-diffusion high-order Cohen-Grossberg-type BAM neural networks with delays
Abstract: In this paper, the mean square exponential stability of the periodic solution for stochastic reactiondiffusion high-order Cohen-Grossberg-Type BAM neural networks with time delays is investigated. By constructing suitable Lyapunov function, applying Itô formula and Poincaré mapping, we give some sufficient conditions to guarantee the mean square exponential stability of the periodic s...
متن کاملPeriodic Solutions of a Cohen-Grossberg-Type BAM Neural Networks with Distributed Delays and Impulses
A class of Cohen-Grossberg-type BAM neural networks with distributed delays and impulses are investigated in this paper. Sufficient conditions to guarantee the uniqueness and global exponential stability of the periodic solutions of such networks are established by using suitable Lyapunov function, the properties of M-matrix, and some suitable mathematical transformation. The results in this pa...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014