Inner Synchronization of Complex‐Valued Stochastic Coupled Networks Via Intermittent Discrete Observation Control

ABSTRACT To investigate the inner synchronization of stochastic complex‐valued coupled networks, a hybrid control method named aperiodically intermittent discrete observation control (AIDOC) is proposed in the sense of average, which combines the merits of discrete time state observation control and aperiodically intermittent control. By using the average technique, the minimum control ratio condition, quasi‐periodicity condition is not required, which makes our results more general and less conservative. Moreover, by employing the Lyapunov method and graph theory, some sufficient conditions are given to guarantee the realization of the synchronization. Then, the inner synchronization of stochastic complex‐valued coupled oscillators (SCCOs) is considered via AIDOC. Eventually, several numerical simulations are given to testify the effectiveness of the results developed.

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Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2025-11-03
DOI
https://doi.org/10.1002/mma.70294
Primary Topic
Neural Networks Stability and Synchronization
Type
article
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0.00
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article

Inner Synchronization of Complex‐Valued Stochastic Coupled Networks Via Intermittent Discrete Observation Control

Guang Dai, Wenbin Hu, Yan Liu
Mathematical Methods in the Applied Sciences
Neural Networks Stability and Synchronization
article

Inner Synchronization of Complex‐Valued Stochastic Coupled Networks Via Intermittent Discrete Observation Control

Guang Dai, Wenbin Hu, Yan Liu
article en

Abstract

ABSTRACT To investigate the inner synchronization of stochastic complex‐valued coupled networks, a hybrid control method named aperiodically intermittent discrete observation control (AIDOC) is proposed in the sense of average, which combines the merits of discrete time state observation control and aperiodically intermittent control. By using the average technique, the minimum control ratio condition, quasi‐periodicity condition is not required, which makes our results more general and less conservative. Moreover, by employing the Lyapunov method and graph theory, some sufficient conditions are given to guarantee the realization of the synchronization. Then, the inner synchronization of stochastic complex‐valued coupled oscillators (SCCOs) is considered via AIDOC. Eventually, several numerical simulations are given to testify the effectiveness of the results developed.

Mathematical Methods in the Applied SciencesVol. 49(4)
Tianjin University of Technology (CN), Tiangong University (CN), Weihai Science and Technology Bureau (CN)
Openalex Percentile: Top 62%
Neural Networks Stability and Synchronization
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