Topology Identification and Module–Phase Synchronization of Neural Network With Time Delay
针对一类具有不确定拓扑权重和有界时滞的神经网络，研究了模-相同步问题，通过构造Lyapunov-Krasovskii泛函和自适应反馈控制，给出了实现同步的充分条件，并讨论了拓扑识别下的同步。
This paper presents the module-phase synchronization for a class of neural networks with weights identification and time delays. In module-phase synchronization, complex-valued node states are taken into consideration. The topology weights considered here are uncertain and the time delays are bounded. By constructing a Lyapunov-Krasovskii functional and employing adaptive feedback control, sufficient conditions for module-phase synchronization are derived. After the general synchronization theory, the synchronization with topology identification is discussed. Finally, pertinent examples are given to demonstrate the effectiveness of the obtained results.