Fixed‐time synchronization of neural networks with time delay via quantized intermittent control
Wenqiang Yang, Junjian Huang, Shiping Wen, Xing He
Abstract
Abstract This paper presents an approach for fixed‐time synchronization (FIXTS) of neural networks (NNs) by designing quantized intermittent controller. Under the intermittent controller, the synchronization between neural network systems with time delay can be realized. Based on intermittent strategy, FIXTs theory is proposed, and a sufficient condition is established to realize the FIXTS of the master–slave NNs. At the same time, the establishment time of FIXTS is estimated. Finally, the simulation of Gilli attractor to prove the validity of the proposed method.
Topics & Concepts
Synchronization (alternating current)Control theory (sociology)AttractorArtificial neural networkController (irrigation)Intermittent controlComputer scienceDiscrete time and continuous timeControl (management)MathematicsControl engineeringEngineeringArtificial intelligenceTelecommunicationsAgronomyMathematical analysisBiologyStatisticsChannel (broadcasting)Neural Networks Stability and SynchronizationAdvanced Memory and Neural ComputingDistributed Control Multi-Agent Systems