Stability and synchronization for discrete-time complex-valued neural networks with time-varying delays

Hao Zhang; Xing-yuan Wang; Xiao-hui Lin; Chong-xin Liu

doi:10.1371/journal.pone.0093838

Stability and synchronization for discrete-time complex-valued neural networks with time-varying delays

PLoS One. 2014 Apr 8;9(4):e93838. doi: 10.1371/journal.pone.0093838. eCollection 2014.

Authors

Hao Zhang¹, Xing-yuan Wang¹, Xiao-hui Lin¹, Chong-xin Liu²

Affiliations

¹ Faculty of Electronic Information & Electrical Engineering, Dalian University of Technology, Dalian, China.
² Institute of Electrical Engineering, Xi'an Jiaotong University, Xi'an, China.

Abstract

In this paper, the synchronization problem for a class of discrete-time complex-valued neural networks with time-varying delays is investigated. Compared with the previous work, the time delay and parameters are assumed to be time-varying. By separating the real part and imaginary part, the discrete-time model of complex-valued neural networks is derived. Moreover, by using the complex-valued Lyapunov-Krasovskii functional method and linear matrix inequality as tools, sufficient conditions of the synchronization stability are obtained. In numerical simulation, examples are presented to show the effectiveness of our method.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Computer Simulation*
Neural Networks, Computer*
Time Factors

Grants and funding

This research is supported by the National Natural Science Foundation of China (Nos: 61370145, 61173183, and 60973152), the Doctoral Program Foundation of Institution of Higher Education of China (No: 20070141014), Program for Liaoning Excellent Talents in University (No: LR2012003), the National Natural Science Foundation of Liaoning province (No: 20082165) and the Fundamental Research Funds for the Central Universities (No: DUT12JB06). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.