School of Mathematical Sciences, Huaqiao University, Quanzhou 362021, Fujian, People's Republic of China.
College of Mathematics and Econometrics, Hunan University, Changsha 410082, Hunan, People's Republic of China.
Chaos. 2015 Aug;25(8):083103. doi: 10.1063/1.4927737.
This paper is concerned with the synchronization dynamical behaviors for a class of delayed neural networks with discontinuous neuron activations. Continuous and discontinuous state feedback controller are designed such that the neural networks model can realize exponential complete synchronization in view of functional differential inclusions theory, Lyapunov functional method and inequality technique. The new proposed results here are very easy to verify and also applicable to neural networks with continuous activations. Finally, some numerical examples show the applicability and effectiveness of our main results.
本文研究了一类具有间断神经元激活的时滞神经网络的同步动态行为。基于泛函微分包含理论、李雅普诺夫函数方法和不等式技术，设计了连续和间断状态反馈控制器，使得神经网络模型能够实现指数完全同步。这里提出的新结果非常易于验证，也适用于具有连续激活的神经网络。最后，一些数值例子展示了我们主要结果的适用性和有效性。
