Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4974046 | Journal of the Franklin Institute | 2017 | 17 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Hao Zhang, Xing-yuan Wang,