Hybrid enhanced continuous tabu search and genetic algorithm for parameter estimation in colored noise environments

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	Hybrid enhanced continuous tabu search and genetic algorithm for parameter estimation in colored noise environments
	Ramkumar, Barathram 2; Schoen, Marco P.1; Lin, Feng 3
刊名	EXPERT SYSTEMS WITH APPLICATIONS
	2011-04-01
卷号	38 期号:4 页码:3909-3917
关键词	Tabu search Genetic algorithm Parameter estimation
英文摘要	Parameter estimation is an important concept in engineering where a mathematical model of a system is identified with the help of input and output signals. Classical parameter estimation algorithms such as Least Squares (LS), Recursive Least Squares (RLS), Least Mean Squares (LMS) and Generalized Least Squares (GLS) give an unbiased estimate of the parameters when the system noise is white. This property is lost when the system noise is colored which is generally the case for many practical situations. In order to overcome the bias problem associated with the colored noise environment, one can use a whitening filter. The cost function of the estimation problem in the case of a colored noise environment becomes multimodal when the signal to noise ratio is high. Hence the motivation to use some intelligent optimization technique for the purpose of finding the global minimum of the parameter estimation problem. A new hybrid algorithm combining intelligent optimization techniques, i.e. enhanced continuous tabu search (ECTS) and elitism based genetic algorithm (GA) is proposed and is applied to the parameter estimation problem. In this work, the ECTS is used to define smaller search spaces, which are investigated in a second stage by a GA to find the respective local minima. Simulation results show that the parameters estimated using the proposed algorithm is unbiased in the presence colored noise. In addition, the hybrid algorithm is also tested with known multimodal benchmark problems. (C) 2010 Elsevier Ltd. All rights reserved.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
研究领域[WOS]	Computer Science ; Engineering ; Operations Research & Management Science
关键词[WOS]	GLOBAL OPTIMIZATION
收录类别	SCI
语种	英语
WOS记录号	WOS:000286904600110
公开日期	2015-12-22
内容类型	期刊论文
源URL	[http://ir.etp.ac.cn/handle/311046/106552]
专题	工程热物理研究所_中国科学院工程热物理所（论文库）_期刊论文（SCI）
作者单位	1.Idaho State Univ, Dept Mech Engn, Coll Engn, Pocatello, ID 83209 USA 2.Idaho State Univ, MCERC, Coll Engn, Pocatello, ID 83209 USA 3.Chinese Acad Sci, Inst Engn Thermophys, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Ramkumar, Barathram,Schoen, Marco P.,Lin, Feng. Hybrid enhanced continuous tabu search and genetic algorithm for parameter estimation in colored noise environments[J]. EXPERT SYSTEMS WITH APPLICATIONS,2011,38(4):3909-3917.
APA	Ramkumar, Barathram,Schoen, Marco P.,&Lin, Feng.(2011).Hybrid enhanced continuous tabu search and genetic algorithm for parameter estimation in colored noise environments.EXPERT SYSTEMS WITH APPLICATIONS,38(4),3909-3917.
MLA	Ramkumar, Barathram,et al."Hybrid enhanced continuous tabu search and genetic algorithm for parameter estimation in colored noise environments".EXPERT SYSTEMS WITH APPLICATIONS 38.4(2011):3909-3917.