Almost Periodicity in Impulsive Fractional-Order Reaction–Diffusion Neural Networks With Time-Varying Delays
Jinde Cao, Gani Stamov, Ivanka Stamova, Stanislav Simeonov
Abstract
A neural-network model of fractional order with impulsive perturbations, time-varying delays, and reaction-diffusion terms is investigated in this article. The focus is on investigating qualitative properties of the states and developing new almost periodicity and stability criteria. The uncertain case is also considered. Examples are established and the effectiveness of the obtained criteria is demonstrated.
Topics & Concepts
Reaction–diffusion systemArtificial neural networkOrder (exchange)Stability (learning theory)DiffusionFocus (optics)Applied mathematicsMathematicsControl theory (sociology)Computer scienceMathematical analysisPhysicsEconomicsArtificial intelligenceThermodynamicsMachine learningControl (management)FinanceOpticsNeural Networks Stability and SynchronizationFractional Differential Equations SolutionsNeural Networks and Applications