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LMI Conditions for Global Stability of Fractional-Order Neural Networks
Zhang, Shuo1; Yu, Yongguang1; Yu, Junzhi2
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2017-10-01
Volume28Issue:10Pages:2423-2433
SubtypeArticle
AbstractFractional-order neural networks play a vital role in modeling the information processing of neuronal interactions. It is still an open and necessary topic for fractional-order neural networks to investigate their global stability. This paper proposes some simplified linear matrix inequality (LMI) stability conditions for fractional-order linear and nonlinear systems. Then, the global stability analysis of fractional-order neural networks employs the results from the obtained LMI conditions. In the LMI form, the obtained results include the existence and uniqueness of equilibrium point and its global stability, which simplify and extend some previous work on the stability analysis of the fractional-order neural networks. Moreover, a generalized projective synchronization method between such neural systems is given, along with its corresponding LMI condition. Finally, two numerical examples are provided to illustrate the effectiveness of the established LMI conditions.
KeywordFractional Order Generalized Projective Synchronization (Gps) Linear Matrix Inequality (Lmi) Neural Networks Stability
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TNNLS.2016.2574842
WOS KeywordOPTIMIZATION PROBLEMS ; DISTRIBUTED DELAYS ; NONLINEAR-SYSTEMS ; TIME DELAYS ; SYNCHRONIZATION ; DISCRETE ; MODEL ; DYNAMICS ; NEURONS ; CHAOS
Indexed BySCI
Language英语
Funding OrganizationFundamental Research Funds for the Central Universities(2016JBM070) ; National Natural Science Foundation of China(11371049 ; 61375102)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000411293200017
Citation statistics
Cited Times:27[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13080
Collection复杂系统管理与控制国家重点实验室_先进机器人
Corresponding AuthorYu, Yongguang
Affiliation1.Beijing Jiaotong Univ, Dept Math, Sch Sci, Beijing 100044, Peoples R China
2.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Shuo,Yu, Yongguang,Yu, Junzhi. LMI Conditions for Global Stability of Fractional-Order Neural Networks[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2017,28(10):2423-2433.
APA Zhang, Shuo,Yu, Yongguang,&Yu, Junzhi.(2017).LMI Conditions for Global Stability of Fractional-Order Neural Networks.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,28(10),2423-2433.
MLA Zhang, Shuo,et al."LMI Conditions for Global Stability of Fractional-Order Neural Networks".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 28.10(2017):2423-2433.
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