Research On Almost Periodic Solutions Of Several Kinds Of Neural Network Models

In this paper,we use the method of non-decomposition to study the existence and global exponential stability of p-th Weyl almost periodic solutions in distribution of Clifford-valued stochastic high-order Hopfield neural networks with time-varying delays and the existence the almost periodic solutions in distribution for a class of Clifford-valued stochastic recurrent neural networks with time-varying delays..First,we use Banach fixed point theorem and inequality techniques to study the existence and uniqueness of p-th Weyl almost periodic solutions in distribution of the high-order Hopfield neural networks and the almost periodic solutions in distribution of recurrent neural networks.Then we use reduction to absurdity to prove the global exponential stability in p-th mean of this unique p-th Weyl almost periodic solution in distribution of the high-order Hopfield neural networks and the global exponential stability of this unique almost periodic solution in distribution of the recurrent neural networks.Even if the neural networks we consider degenerate into a real-valued neural network,our results are new.Finally,we give numerical examples to examine the effectiveness of our theoretical results.