Robustness analysis of a hybrid of recursive neural dynamics for online matrix inversion

	Robustness analysis of a hybrid of recursive neural dynamics for online matrix inversion
	Chen, Ke; Yi, Chenfu
刊名	APPLIED MATHEMATICS AND COMPUTATION
	2016
英文摘要	Encouraged by superior convergence performance achieved by a recently proposed hybrid of recursive neural dynamics for online matrix inversion, we investigate its robustness properties in this paper when there exists large rnodel implementation errors. Theoretical analysis shows that the perturbed dynamic system is still global stable with the tight steady-state bound of solution error estimated. Moreover, this paper analyses global exponential convergence rate and finite convergence time of such a hybrid dynamical model to a relatively loose solution error bound. Computer simulation results substantiate our analysis on the perturbed hybrid neural dynamics for online matrix inversion when having large implementation errors. (C) 2015 Elsevier Inc. All rights reserved.
收录类别	SCI
原文出处	http://www.sciencedirect.com/science/article/pii/S0096300315013685
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/10390]
专题	深圳先进技术研究院_医工所
作者单位	APPLIED MATHEMATICS AND COMPUTATION
推荐引用方式 GB/T 7714	Chen, Ke,Yi, Chenfu. Robustness analysis of a hybrid of recursive neural dynamics for online matrix inversion[J]. APPLIED MATHEMATICS AND COMPUTATION,2016.
APA	Chen, Ke,&Yi, Chenfu.(2016).Robustness analysis of a hybrid of recursive neural dynamics for online matrix inversion.APPLIED MATHEMATICS AND COMPUTATION.
MLA	Chen, Ke,et al."Robustness analysis of a hybrid of recursive neural dynamics for online matrix inversion".APPLIED MATHEMATICS AND COMPUTATION (2016).