A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 复杂系统智能机理与平行控制团队

	A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks
	Zhang, Huaguang 1,2; Wang, Zhanshan 1,2; Liu, Derong 3
发表期刊	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
	2014-07-01
卷号	25 期号:7 页码:1229-1262
文章类型	Review
摘要	Stability problems of continuous-time recurrent neural networks have been extensively studied, and many papers have been published in the literature. The purpose of this paper is to provide a comprehensive review of the research on stability of continuous-time recurrent neural networks, including Hopfield neural networks, Cohen-Grossberg neural networks, and related models. Since time delay is inevitable in practice, stability results of recurrent neural networks with different classes of time delays are reviewed in detail. For the case of delay-dependent stability, the results on how to deal with the constant/variable delay in recurrent neural networks are summarized. The relationship among stability results in different forms, such as algebraic inequality forms, M-matrix forms, linear matrix inequality forms, and Lyapunov diagonal stability forms, is discussed and compared. Some necessary and sufficient stability conditions for recurrent neural networks without time delays are also discussed. Concluding remarks and future directions of stability analysis of recurrent neural networks are given.
关键词	Cohen-grossberg Neural Networks Discrete Delay Distributed Delays Hopfield Neural Networks Linear Matrix Inequality (Lmi) Lyapunov Diagonal Stability (Lds) M-matrix Recurrent Neural Networks Robust Stability Stability
WOS标题词	Science & Technology ; Technology
关键词[WOS]	GLOBAL ASYMPTOTIC STABILITY ; ABSOLUTE EXPONENTIAL STABILITY ; DESCRIPTOR SYSTEM APPROACH ; DELAY-DEPENDENT STABILITY ; REACTION-DIFFUSION TERMS ; H-INFINITY CONTROL ; COHEN-GROSSBERG MODEL ; DISCONTINUOUS ACTIVATION FUNCTIONS ; FUNCTIONAL-DIFFERENTIAL EQUATIONS ; DERIVING SUFFICIENT CONDITIONS
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号	WOS:000337906300001
引用统计	被引频次：503[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3839
专题	多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队
作者单位	1.Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110004, Peoples R China 2.State Key Lab Synthet Automat Proc Ind, Shenyang 110004, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Huaguang,Wang, Zhanshan,Liu, Derong. A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2014,25(7):1229-1262.
APA	Zhang, Huaguang,Wang, Zhanshan,&Liu, Derong.(2014).A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,25(7),1229-1262.
MLA	Zhang, Huaguang,et al."A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 25.7(2014):1229-1262.