Nonconvex stochastic optimization for model reduction

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	Nonconvex stochastic optimization for model reduction
	Chen, HF; Fang, HT
	2002-08-01
发表期刊	JOURNAL OF GLOBAL OPTIMIZATION
ISSN	0925-5001
卷号	23 期号:3-4 页码:359-372
摘要	In this paper a global stochastic optimization algorithm, which is almost surely (a.s.) convergent, is applied to the model reduction problem. The proposed method is compared with the balanced truncation and Hankel norm approximation methods by examples in step responses and in approximation errors as well. Simulation shows that the proposed algorithm provides better results.
关键词	stochastic optimization model reduction balanced truncation Hankel norm approximation
语种	英语
WOS研究方向	Operations Research & Management Science ; Mathematics
WOS类目	Operations Research & Management Science ; Mathematics, Applied
WOS记录号	WOS:000177101700009
出版者	KLUWER ACADEMIC PUBL
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/17607
专题	中国科学院数学与系统科学研究院
通讯作者	Chen, HF
作者单位	Chinese Acad Sci, Lab Syst & Control, Inst Syst Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Chen, HF,Fang, HT. Nonconvex stochastic optimization for model reduction[J]. JOURNAL OF GLOBAL OPTIMIZATION,2002,23(3-4):359-372.
APA	Chen, HF,&Fang, HT.(2002).Nonconvex stochastic optimization for model reduction.JOURNAL OF GLOBAL OPTIMIZATION,23(3-4),359-372.
MLA	Chen, HF,et al."Nonconvex stochastic optimization for model reduction".JOURNAL OF GLOBAL OPTIMIZATION 23.3-4(2002):359-372.