Stability and synchronization of fractional-order complex-valued neural networks with time delay: LMI approach
Department of Mathematics, Bharathiar University,
Tamil Nadu, India
2 Department of Mathematical Sciences, College of Science, UAE University, 15551 Al-Ain, United Arab Emirates
Received in final form: 28 September 2017
Published online: 25 July 2018
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.
© EDP Sciences, Springer-Verlag 2018