Synchronizations of fuzzy cellular neural networks with proportional time-delay

In this article, finite-time and fixed-time synchronizations (FFTS) of fuzzy cellular neural networks (FCNNs) with interaction and proportional delay terms have been investigated. The synchronizations of FCNNs are achieved with the help of p-norm based on the inequalities defined in Lemmas 2.1 and 2.2. The analysis of the method with some useful criteria is also used during the study of FFTS. Under the Lyapunov stability theory, FFTS of fuzzy-based CNNs with interaction and proportional delay terms can be achieved using controllers. Moreover, the upper bound of the settling time of FFTS is obtained. In view of settling points, the theoretical results on the considered neural network models of this article are more general as compared to the fixed time synchronization (FTS). The effectiveness and reliability of the theoretical results are shown through two numerical examples for different particular cases.

Automated summary

This article investigates finite-time and fixed-time synchronizations of fuzzy cellular neural networks with interaction and proportional delay terms. Synchronization is achieved using p-norm based on defined inequalities, and Lyapunov stability theory and controllers are utilized to achieve FFTS with an upper bound on settling time. The theoretical results are shown to be more general compared to fixed time synchronization through numerical examples.