Anti-synchronization Analysis of Fractional-Order Neural Networks with Time-Varying Delays
Minglin Xu, Peng Liu, Minxue Kong, Junwei Sun · 2020
This paper deals with the anti-synchronization problem of fractional-order neural networks with time-varying delays. By using the properties of fractional calculus, sufficient criteria are deduced for realizing the anti-synchronization of fractional-order neural networks with time-varying delays. In addition, sufficient criteria for anti-synchronization in Mittag-Leffler sense are derived for fractional-order neural networks without time delay. The results in this paper are also applicable for anti-synchronization results of integer-order neural networks. Three numerical examples are proposed to verify the validity of the theoretical results.