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New Adaptive Finite-Time Cluster Synchronization of Neutral-Type Complex-Valued Coupled Neural Networks with Mixed Time Delays

N. Boonsatit, Santhakumari Rajendran, Chee Peng Lim, Anuwat Jirawattanapanit, Praneesh Mohandas

2022Fractal and Fractional19 citationsDOIOpen Access PDF

Abstract

The issue of adaptive finite-time cluster synchronization corresponding to neutral-type coupled complex-valued neural networks with mixed delays is examined in this research. A neutral-type coupled complex-valued neural network with mixed delays is more general than that of a traditional neural network, since it considers distributed delays, state delays and coupling delays. In this research, a new adaptive control technique is developed to synchronize neutral-type coupled complex-valued neural networks with mixed delays in finite time. To stabilize the resulting closed-loop system, the Lyapunov stability argument is leveraged to infer the necessary requirements on the control factors. The effectiveness of the proposed method is illustrated through simulation studies.

Topics & Concepts

Artificial neural networkSynchronization (alternating current)Control theory (sociology)Computer scienceType (biology)Adaptive controlStability (learning theory)Coupling (piping)Cluster (spacecraft)Control (management)Artificial intelligenceEngineeringMachine learningProgramming languageMechanical engineeringComputer networkBiologyEcologyChannel (broadcasting)Neural Networks Stability and SynchronizationDistributed Control Multi-Agent SystemsAdvanced Memory and Neural Computing
New Adaptive Finite-Time Cluster Synchronization of Neutral-Type Complex-Valued Coupled Neural Networks with Mixed Time Delays | Litcius