A stabilization approach for a novel chaotic fractional-order discrete neural network
Unknown authors
Abstract
This paper aims to make a contribution to the topic of the stabilization of chaotic dynamics in fractional-order discrete systems by presenting a novel three-dimensional fractional-order discrete neural network formulated by the h-fractional difference operator. A novel theorem is illustrated with the aim of stabilizing the chaotic trajectories of the three-dimensional fractional-order discrete neural network at zero through proposing a quite simple linear control laws. Finally, certain simulation results are carried out to highlight the effectiveness of the stabilization approach proposed herein.
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MathematicsChaoticArtificial neural networkOrder (exchange)Control theory (sociology)Simple (philosophy)Operator (biology)Applied mathematicsZero (linguistics)Chaotic systemsControl (management)Computer scienceArtificial intelligenceEconomicsRepressorChemistryEpistemologyTranscription factorFinanceBiochemistryPhilosophyLinguisticsGeneNeural Networks and ApplicationsNeural Networks Stability and SynchronizationChaos control and synchronization