Sampled-Data-Based Bipartite Leader-Follower Synchronization of Cooperation-Competition Neural Networks via Interval-Scheduled Looped-Functions

This paper addresses the bipartite leader-follower synchronization (BLFS) of cooperation-competition neural networks (CCNNs) via sampled-data (SD) control. First, the directed signed graph (SG) theory is applied to describe the cooperation and competition interactions, and thus, an appropriate mathe...

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Veröffentlicht in:	IEEE transactions on circuits and systems. I, Regular papers Regular papers, 2023-09, Vol.70 (9), p.1-12
Hauptverfasser:	Si, Xindong, Wang, Zhen, Fan, Yingjie, Huang, Xia, Shen, Hao
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Asymptotic stability bipartite leader-follower synchronization Competition Cooperation Cooperation-competition neural networks Coordinate transformations coupling strength Couplings looped-function method Mathematical analysis Mathematical models Neural networks sampled-data control State feedback Symmetric matrices Synchronism Synchronization
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