Stabilization and synchronization control of quaternion-valued fuzzy memristive neural networks: Nonlinear scalarization approach

Abstract

In this paper, we present new conditions ensuring existence, uniqueness, and stabilization of the equilibrium point (EP) for a large class of quaternion-valued memristive neural networks. The results are applicable to both complex-valued memristive neural networks and quaternion-valued system with uncertain terms. Subsequently, by employing suitable controller, the synchronization control conclusion is also considered. It is worth mentioning that, the nonlinear scalarization approach is employed to ensure the closed convex hull consisted by the quaternion is meaningful, which preserves the integrity of the quaternion system and makes the conclusion more reasonable. Finally, this paper provides two examples, so that the superiority of the main results can be illustrated.