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

Feifei Du, Jun‐Guo Lu

2020IEEE Transactions on Neural Networks and Learning Systems62 citationsDOI

Abstract

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 was divided into two cases: λ ∈ (0,0.5] and λ ∈ (0.5,+∞) . In this article, a new fractional-order Gronwall integral inequality with time delay and the unified form for all the fractional order 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 λ ∈ (0,1) was divided into two cases, λ ∈ (0,0.5] and λ ∈ (0.5,1) , the obtained results in this article are presented in the unified form of fractional order λ ∈ (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.

Topics & Concepts

Stability (learning theory)Gronwall's inequalityOrder (exchange)Artificial neural networkMathematicsApplied mathematicsHopfield networkFunction (biology)Fractional calculusInequalityComputer scienceControl theory (sociology)Mathematical optimizationMathematical analysisArtificial intelligenceFinanceMachine learningControl (management)EconomicsEvolutionary biologyBiologyNeural Networks Stability and SynchronizationNeural Networks and Applicationsstochastic dynamics and bifurcation