Bipartite Synchronization of Fractional-Order Memristor-Based Coupled Delayed Neural Networks with Pinning Control
P. Babu Dhivakaran, A. Vinodkumar, S. Dinesh Vijay, S. Lakshmanan, Jehad Alzabut, Rami Ahmad El‐Nabulsi, Waranont Anukool
Abstract
This paper investigates the bipartite synchronization of memristor-based fractional-order coupled delayed neural networks with structurally balanced and unbalanced concepts. The main result is established for the proposed model using pinning control, fractional-order Jensen’s inequality, and the linear matrix inequality. Further, new sufficient conditions are derived using the Lyapunov–Krasovskii functional with delay-dependent criteria. Finally, numerical simulations are provided including two numerical examples to show the effectiveness of the theoretical results.
Topics & Concepts
MemristorSynchronization (alternating current)Artificial neural networkControl theory (sociology)Bipartite graphOrder (exchange)MathematicsLinear matrix inequalityControl (management)Applied mathematicsTopology (electrical circuits)Computer scienceMathematical optimizationDiscrete mathematicsPhysicsArtificial intelligenceCombinatoricsGraphFinanceQuantum mechanicsEconomicsNeural Networks Stability and SynchronizationDistributed Control Multi-Agent SystemsNonlinear Dynamics and Pattern Formation