Stability Of Bam Neural Networks With Time Delay Analysis

Neural networks were used for reality of all kinds broadly over the past few years, for instance: Design associative memory and resolve the optimization problem. If neural networks are used to solve a optimize problem, the system need a unique equilibrium point of globally asymptotic stability. Therefore, many persons have produced very big interest to the affirming of the condition of the neural networks stability, and at present many papers have been focus on the stability of the equilibrium point of the neural networks and have given the uniqueness and globally asymptotic stability of different neural networks models out. On the other hand, it is also very important to use the delay character of neural to solve the optimization problem relevant dynamic. Especially the stability of BAM neural networks with time delays has caught more attention. The paper mainly studied that the stability problem of BAM neural networks with time delays, first it studied the uniqueness and globally asymptotic stability of continuous BAM neural networks, the second the uniqueness and exponential stability of BAM neural networks with continuous time delays, the last the uniqueness and globally asymptotic stability of BAM neural networks with both continuous and discrete times delays.Include the following content concretely:1 studied the stability of the continuous BAM neural networks. Using Lyapunov method, it gives the conditions of the uniqueness and globally asymptotic stability of continuous BAM neural networks, respectively .And the example is given to some results and verified.2 studied the uniqueness and exponential stability of BAM neural networks with continuous time delays. Using contradiction and the method for variation of parameters, it gives the conditions of the uniqueness and exponential stability of BAM neural networks with continuous time delays, respectively. And the example is given to some results and verified.3 studied the uniqueness and globally asymptotic stability of BAM neural networks with both continuous and discrete time delays. Using the skill of inequality and Lyapunov method, it gives the conditions of the uniqueness and globally asymptotic stability of continuous BAM neural networks, respectively. And the example is given to some results and verified.Now the documents which the solution and stability of BAM neural networks with continuous and discrete are less, which will have large difficulties, and we will solute the problems by building Lyapunov functional and LMI skill. The paper changed the singleness of inequality among enlarging the derivative of Lyapunov functional, and reduced the conservative of the current documents conclusion. Some documents have studied BAM neural networks with time delays, but the study of the stability of BAM neural networks with both continuous and discrete time delays is less. The paper has done some studies.