Eur. Phys. J. Special Topics 226, 3639–3655 (2017)
https://doi.org/10.1140/epjst/e2018-00066-0

Regular Article

Stability and synchronization of fractional-order complex-valued neural networks with time delay: LMI approach

¹ Department of Mathematics, Bharathiar University, Coimbatore 641 046, Tamil Nadu, India
² Department of Mathematical Sciences, College of Science, UAE University, 15551 Al-Ain, United Arab Emirates

Received: 1 August 2017
Received in final form: 28 September 2017
Published online: 25 July 2018

Abstract

In this paper, we investigate the problem of stability and synchronization of fractional-order complex-valued neural networks with time delay. By using Lyapunov–Krasovskii functional approach, some linear matrix inequality (LMI) conditions are proposed to ensure that the equilibrium point of the addressed neural networks is globally Mittag–Leffler stable. Moreover, some sufficient conditions for projective synchronization of considered fractional-order complex-valued neural networks are derived in terms of LMIs. Finally, two numerical examples are given to demonstrate the effectiveness of our theoretical results.