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Adaptive Synchronization of Fractional-Order Output-Coupling Neural Networks via Quantized Output Control

Haibo Bao, Ju H. Park, Jinde Cao

2020IEEE Transactions on Neural Networks and Learning Systems169 citationsDOIOpen Access PDF

Abstract

This article focuses on the adaptive synchronization for a class of fractional-order coupled neural networks (FCNNs) with output coupling. The model is new for output coupling item in the FCNNs that treat FCNNs with state coupling as its particular case. Novel adaptive output controllers with logarithm quantization are designed to cope with the stability of the fractional-order error systems for the first attempt, which is also an effective way to synchronize fractional-order complex networks. Based on fractional-order Lyapunov functionals and linear matrix inequalities (LMIs) method, sufficient conditions rather than algebraic conditions are built to realize the synchronization of FCNNs with output coupling. A numerical simulation is put forward to substantiate the applicability of our results.

Topics & Concepts

Control theory (sociology)Synchronization (alternating current)Artificial neural networkQuantization (signal processing)Coupling (piping)LogarithmComputer scienceLyapunov stabilityAdaptive controlStability (learning theory)Algebraic numberMathematicsControl (management)Topology (electrical circuits)AlgorithmEngineeringMathematical analysisArtificial intelligenceMachine learningCombinatoricsMechanical engineeringNeural Networks Stability and SynchronizationNeural Networks and ApplicationsAdvanced Memory and Neural Computing
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