A fast fixed-point algorithm for complexity pursuit
Shi, ZW; Tang, HW; Tang, YY
2005-03-01
发表期刊NEUROCOMPUTING
ISSN0925-2312
文章类型Article
卷号64页码:529-536
摘要Complexity pursuit is a recently developed algorithm using the gradient descent for separating interesting components from time series. It is an extension of projection pursuit to time series data and the method is closely related to blind separation of time-dependent source signals and independent component analysis (ICA). In this paper, a fixed-point algorithm for complexity pursuit is introduced. The fixed-point algorithm inherits the advantages of the well-known FastICA algorithm in ICA, which is very simple, converges fast, and does not need choose any learning step sizes. (c) 2005 Elsevier B.V. All rights reserved.
关键词independent component analysis blind source separation complexity pursuit projection pursuit time series
收录类别SCI
语种英语
WOS记录号WOS:000227922700031
引用统计
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/14070
专题中国科学院心理研究所回溯数据库(1956-2010)
作者单位1.Dalian Univ Technol, Inst Computat Biol & Bioinformat, Dalian 116023, Peoples R China
2.Dalian Univ Technol, Inst Neuroinformat, Dalian 116023, Peoples R China
3.Chinese Acad Sci, Lab Visual Informat Proc, Beijing 100101, Peoples R China
4.Chinese Acad Sci, Key Lab Mental Hlth, Beijing 100101, Peoples R China
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Shi, ZW,Tang, HW,Tang, YY. A fast fixed-point algorithm for complexity pursuit[J]. NEUROCOMPUTING,2005,64:529-536.
APA Shi, ZW,Tang, HW,&Tang, YY.(2005).A fast fixed-point algorithm for complexity pursuit.NEUROCOMPUTING,64,529-536.
MLA Shi, ZW,et al."A fast fixed-point algorithm for complexity pursuit".NEUROCOMPUTING 64(2005):529-536.
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