An analysis on existence and global exponential stability of periodic solutions for BAM neural networks with time-varying delays

In this paper, the problem on periodic solutions of the bidirectional associative memory neural networks with both periodic coefficients and periodic time-varying delays is discussed. By using analytic methods, inequality technique and M-matrix theory, several sufficient conditions ensuring the existence, uniqueness, and global exponential stability of periodic solution are derived. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. Some existing results are improved and extended. The obtained results are less restrictive than previously known criteria, and the hypothesis for the boundedness and monotonicity on the activation functions and the differentiability on the time-varying delays are removed. An example is given to show the effectiveness of the obtained results.