{"title":"扩散耦合非线性网络中集群同步努力的最小控制","authors":"Jinkui Zhang , Shidong Zhai , Wei Zhu","doi":"10.1016/j.neucom.2024.128841","DOIUrl":null,"url":null,"abstract":"<div><div>This paper studies the design of minimal control effort for cluster synchronization (CS) in a diffusion-coupled nonlinear network under directed graph. Under the conditions that the directed graph satisfies the cluster input equivalence condition and the system possesses a bounded Jacobian matrix, we obtain CS of diffusion-coupled nonlinear network with non-diagonal coupling matrix. Based on matrix measure and balancing theorem, we obtain the local minimization controllers for the minimal control effort of CS. Finally, the theoretical results are validated through a numerical example involving a network of coupled FitzHugh–Nagumo neurons with a general topology of interactions.</div></div>","PeriodicalId":19268,"journal":{"name":"Neurocomputing","volume":"614 ","pages":"Article 128841"},"PeriodicalIF":5.5000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Minimum control of cluster synchronization effort in diffusion coupled nonlinear networks\",\"authors\":\"Jinkui Zhang , Shidong Zhai , Wei Zhu\",\"doi\":\"10.1016/j.neucom.2024.128841\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper studies the design of minimal control effort for cluster synchronization (CS) in a diffusion-coupled nonlinear network under directed graph. Under the conditions that the directed graph satisfies the cluster input equivalence condition and the system possesses a bounded Jacobian matrix, we obtain CS of diffusion-coupled nonlinear network with non-diagonal coupling matrix. Based on matrix measure and balancing theorem, we obtain the local minimization controllers for the minimal control effort of CS. Finally, the theoretical results are validated through a numerical example involving a network of coupled FitzHugh–Nagumo neurons with a general topology of interactions.</div></div>\",\"PeriodicalId\":19268,\"journal\":{\"name\":\"Neurocomputing\",\"volume\":\"614 \",\"pages\":\"Article 128841\"},\"PeriodicalIF\":5.5000,\"publicationDate\":\"2024-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neurocomputing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0925231224016126\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurocomputing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0925231224016126","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Minimum control of cluster synchronization effort in diffusion coupled nonlinear networks
This paper studies the design of minimal control effort for cluster synchronization (CS) in a diffusion-coupled nonlinear network under directed graph. Under the conditions that the directed graph satisfies the cluster input equivalence condition and the system possesses a bounded Jacobian matrix, we obtain CS of diffusion-coupled nonlinear network with non-diagonal coupling matrix. Based on matrix measure and balancing theorem, we obtain the local minimization controllers for the minimal control effort of CS. Finally, the theoretical results are validated through a numerical example involving a network of coupled FitzHugh–Nagumo neurons with a general topology of interactions.
期刊介绍:
Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. Neurocomputing theory, practice and applications are the essential topics being covered.