Cluster Synchronization for Coupled Neural Networks with Mixed Couplings via Pinning Partial Impulsive Strategy

This paper explores the issue of cluster synchronization (CS) for coupled neural networks (CNNs) with both current-state coupling and distributed-delay coupling using a pinning partial impulsive control (PPIC) strategy. Considering the synchronization of an array of neural networks featuring two distinct topologies and targeting a desired trajectory while reducing control costs, a novel PPIC strategy is proposed, which selectively controls a specific subset of neurons within certain subnetworks. Finally, the validity of the theoretical analysis and the proposed control scheme is demonstrated through a numerical example.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/icnc64304.2024.10987877
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
0.00

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article

Cluster Synchronization for Coupled Neural Networks with Mixed Couplings via Pinning Partial Impulsive Strategy

Xinle Wang, Xiaoyu Zhang, Hongfei Li
Neural Networks Stability and Synchronization
article

Cluster Synchronization for Coupled Neural Networks with Mixed Couplings via Pinning Partial Impulsive Strategy

Xinle Wang, Xiaoyu Zhang, Hongfei Li
article en

Abstract

This paper explores the issue of cluster synchronization (CS) for coupled neural networks (CNNs) with both current-state coupling and distributed-delay coupling using a pinning partial impulsive control (PPIC) strategy. Considering the synchronization of an array of neural networks featuring two distinct topologies and targeting a desired trajectory while reducing control costs, a novel PPIC strategy is proposed, which selectively controls a specific subset of neurons within certain subnetworks. Finally, the validity of the theoretical analysis and the proposed control scheme is demonstrated through a numerical example.

Beijing Foreign Studies University (CN), Southwest University (CN)
Chongqing Municipal Education Commission, Natural Science Foundation of Sichuan Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 64%
Neural Networks Stability and Synchronization
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Cluster Synchronization for Coupled Neural Networks with Mixed Couplings via Pinning Partial Impulsive Strategy — Xinle Wang, Xiaoyu Zhang, et al. · (2024) | TGRS Research Map | TGRS