Complex projective synchronization of complex-valued neural network with structure identification

This paper studies the projective synchronization of neural network in complex-valued domain. Both projective factors and neuron state variables are set as complex values in the synchronization process. In our study, unknown network structure and time-varying delays are considered. With the projective synchronization, the network structure will be identified and the problem of bounded time delays can be solved. With Lyapunov-Krasovskii stability theory and adaptive feedback scheme, controllers are designed and the complex projective synchronization is achieved. In the numerical simulation, several complex-valued neural network examples are provided showing the effectiveness of the theoretical results. (C) 2017 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.