He Wangli, Cao Jinde
Department of Mathematics, Southeast University, Nanjing, China.
IEEE Trans Neural Netw. 2010 Apr;21(4):571-83. doi: 10.1109/TNN.2009.2039803. Epub 2010 Feb 17.
This paper investigates exponential synchronization of coupled networks with hybrid coupling, which is composed of constant coupling and discrete-delay coupling. There is only one transmittal delay in the delayed coupling. The fact is that in the signal transmission process, the time delay affects only the variable that is being transmitted from one system to another, then it makes sense to assume that there is only one single delay contributing to the dynamics. Some sufficient conditions for synchronization are derived based on Lyapunov functional and linear matrix inequality (LMI). In particular, the coupling matrix may be asymmetric or nondiagonal. Moreover, the transmittal delay can be different from the one in the isolated system. A distinctive feature of this work is that the synchronized state will vary in comparison with the conventional synchronized solution. Especially, the degree of the nodes and the inner delayed coupling matrix heavily influence the synchronized state. Finally, a chaotic neural network is used as the node in two regular networks to show the effectiveness of the proposed criteria.
本文研究具有混合耦合的耦合网络的指数同步问题,该混合耦合由常数耦合和离散延迟耦合组成。延迟耦合中仅存在一个传输延迟。事实上,在信号传输过程中,时间延迟仅影响从一个系统传输到另一个系统的变量,因此假设仅有一个单一延迟对动力学有贡献是合理的。基于李雅普诺夫泛函和线性矩阵不等式(LMI)推导了一些同步的充分条件。特别地,耦合矩阵可以是不对称的或非对角的。此外,传输延迟可以不同于孤立系统中的延迟。这项工作的一个显著特点是,与传统的同步解相比,同步状态会有所不同。特别是,节点的度数和内部延迟耦合矩阵对同步状态有很大影响。最后,将一个混沌神经网络用作两个规则网络中的节点,以展示所提准则的有效性。