New Criteria on Finite-Time Stability of Fractional-Order Hopfield Neural Networks With Time Delays

• Published in: IEEE transaction on neural networks and learning systems 2021-09, Vol.32 (9), p.3858-3866
• Main Authors: Du, Feifei, Lu, Jun-Guo
• Format: Article
• Language: English
• Subjects: Asymptotic stability; Delay; Delay effects; Delays; finite-time stability (FTS); fractional order; Gronwall integral inequality; Inequality; Learning systems; neural network; Neural networks; Stability criteria; Time lag; Timing
• ISSN: 2162-237X; 2162-2388
• DOI: 10.1109/TNNLS.2020.3016038

In this article, the finite-time stability (FTS) of fractional-order Hopfield neural networks with time delays (FHNNTDs) is studied. A widely used inequality in investigating the stability of the fractional-order neural networks is fractional-order Gronwall inequality related to the Mittag-Leffler function, which cannot be directly used to study the stability of the factional-order neural networks with time delays. In the existing works related to fractional-order Gronwall inequality with time delays, the order \lambda >0 was divided into two cases: \lambda \in (0,0.5] and \lambda \in (0.5,+\infty) . In this article, a new fractional-order Gronwall integral inequality with time delay and the unified form for all the fractional order \lambda >0 is developed, which can be widely applied to investigate FTS of various fractional-order systems with time delays. Based on this new inequality, a new criterion for the FTS of FHNNTDs is derived. Compared with the existing criteria, in which fractional order \lambda \in (0,1) was divided into two cases, \lambda \in (0,0.5] and \lambda \in (0.5,1) , the obtained results in this article are presented in the unified form of fractional order \lambda \in (0,1) and convenient to verify. More importantly, the criteria in this article are less conservative than some existing ones. Finally, two numerical examples are given to demonstrate the validity of the proposed results.