Dynamics Analysis Of Switched Cohen-Grossberg Neural Networks Model

In recent years, owing to the wide range of potential applications of neural networks both Engineering areas such as pattern recognition, Intelligent Computing, associate memory, Phoneme recognition, knowledge acquisition and the important applications of switched systems, the dynamical issues of switched neural networks have attracted worldwide attention in academics.For the control problem of switched neural networks, it is generally assumed that the switching of the controllers is matched with that of the subsystems, i.e., they are ac-tivated synchronously at switching ruler, we may be regards as synchronously switched systems. However, Some of the complex large systems in practical engineering, since it inevitably takes some time to identify the active subsystem and apply for the matched controller, the switching time of controllers may lag behind that of the correspond-ing subsystems, which leads to asynchronous switching. Therefor, it is necessary and important to investigate the issues of synchronously and asynchronously switching.Studying the problem of dynamics of switched Cohen-Grossberg neural networks(C-GNN) by using Lyapunov functional method, average dwell time (ADT), Linear ma-trix inequalities (LMIs) technique, stochastic analysis technology and extend Jensen inequalities. The main of contents of this paper as following:For delay-dependent switched Cohen-Grossberg neural networks. In previous lit-erature, giving up the assumes of the majority of existing literatures, which the systems have unique equilibrium point. Employ the condition of delay-dependent and Linear matrix inequalities. Some judging criterions on the uniformly ultimate boundedness, the existence of an attractors, the globally exponential stability of systems are devel-oped with ADT, which is closely related to delays. A numerical example is provided to illustrate the effectiveness of the proposed results.The uncertainty switched stochastic Cohen-Grossberg neural networks(SSCGNN) with bounded distributed delays is investigated. Under norm-bounded-parameter un-certainty and noise fluctuations, utilizing tochastic analysis technology, Ito differential formula, LMIs technique and ADT method. A series of sufficient conditions are ob-tained to ensue the stochastic uniformly ultimate boundedness, the existence of an stochastic attractor, and the globally exponential stability in the mean square of SS-CGNN. Eventually, examples illustrate and numerical simulation are carried out by Matlab.The asymptotic behaviors for SSCGNN. under asynchronous switching and vari-eties delays is investigated. The novel sufficient conditions are developed by extending double delay-dependent integral inequality. By dealing with matched and mismatched periods and using LMIs technique, ADT method and Ito differential formula, it make the boundedness, the existence of an attractor, and stability for SSCGNN under asyn-chronous with ADT are guaranteed. At last, numerical simulations show than the the-oretically predicted results are in excellent agreement with the numerically observed behavior.