Exponential stability and synchronization of Memristor-based fractional-order fuzzy cellular neural networks with multiple delays

The stability and synchronization problems are addressed in this study for the memristor-based fractional-order fuzzy cellular neural networks with multiple delays. By using the Laplace transform method, fractional-order calculus approach and the method of complex function, three exponential sta-bility criteria are derived. Compared with the existing results of the above system, the novel exponentially stable and synchronization conditions are first proposed. The obtained results can be applied not only to fractional-order systems, but also to integer-order systems. A two-dimension example and a three-dimension example and a practical example are given to illustrate the validity and merits. (c) 2020 Elsevier B.V. All rights reserved.

Automated summary

This study addresses the stability and synchronization problems for the memristor-based fractional-order fuzzy cellular neural networks with multiple delays. Three exponential stability criteria are derived using Laplace transform method, fractional-order calculus approach, and the method of complex function. Compared with existing results, novel exponentially stable and synchronization conditions have been proposed. The obtained results are applicable to both fractional-order systems and integer-order systems, and their validity and merits are illustrated through examples.