Finite-time synchronization for fuzzy neutral-type inertial neural networks with time-varying coefficients and proportional delays

This paper focuses on the finite-time synchronization for fuzzy neutral-type inertial neural networks with time-varying coefficients and proportional delays. To end this, by choosing proper variable transformation, the original system can be rewritten as the first order differential system. Based on finite-time stability theory and combining with inequality techniques and some analysis methods, some novel delay-independent criteria in terms of algebraic inequalities are obtained to ensure that finite-time synchronization can be achieved between the drive system and the response system by designing two different types of controllers. The criteria here are very simple to implement in practice and avoid complex computation on the matrix inequalities. Moreover, the settling time is also estimated. Finally, two numerical examples with simulations are presented to show the effectiveness of the obtained results. (C) 2019 Elsevier B.V. All rights reserved.