Existence and Global Exponential Stability of Periodic Solutions for General Neural Networks with Time-Varying Delays.

By using the coincidence degree theorem and differential inequality techniques, sufficient conditions are obtained for the existence and global exponential stability of periodic solutions for general neural networks with time-varying (including bounded and unbounded) delays. Some known results are improved and some new results are obtained. An example is employed to illustrate our feasible results. [ABSTRACT FROM AUTHOR]