| Title: | a fixed-point blind source extraction algorithm and its application to ecg data analysis |
| Author: | Zhang Hongjuan
; Wu Zikai
; Ding Shuxue
; Chen Luonan
|
| Source: | 2012 IEEE 6th International Conference on Systems Biology, ISB 2012
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| Conference Name: | 2012 IEEE 6th International Conference on Systems Biology, ISB 2012
|
| Conference Date: | August 18, 2012 - August 20, 2012
|
| Issued Date: | 2012
|
| Conference Place: | Xi'an, China
|
| Keyword: | Algorithms
; Autocorrelation
; Electrocardiography
; Time series
|
| Indexed Type: | EI
|
| ISBN: | 9781467343985
|
| Department: | (1) Department of Mathematics Shanghai University Shanghai 200444 China; (2) Business School University of Shanghai for Science and Technology Shanghai 200093 China; (3) Department of Computer Software University of Aizu Tsuruga Ikki-Machi Aizu-Wakamatsu City Fukushima 965-8580 Japan; (4) Key Laboratory of Systems Biology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Shanghai 200031 China
|
| Sponsorship: | National Natural Science Foundation of China (NSFC); Academy of Mathematics and Systems Sciences of CAS (AMSS); Shanghai Institutes for Biological Sciences of CAS (SIBS); Xidian University; K. C. Wong Education Foundation
|
| Abstract: | Generalized autocorrelations and complexity pursuit are two recently developed methods for extracting interesting component from time series. They are the extensions of projection pursuit to time series data. In this paper, a fixed-point blind source extraction (BSE) algorithm for generalized autocorrelations and complexity pursuit of the desired signals is presented. The fixed-point algorithm inherits the advantages of the well-known FastICA algorithm of ICA, which is very simple, converges fast, and does not need to choose any learning step sizes. Numerical experiments on electrocardiogram (ECG) data indicate its better performance. © 2012 IEEE. |
| English Abstract: | Generalized autocorrelations and complexity pursuit are two recently developed methods for extracting interesting component from time series. They are the extensions of projection pursuit to time series data. In this paper, a fixed-point blind source extraction (BSE) algorithm for generalized autocorrelations and complexity pursuit of the desired signals is presented. The fixed-point algorithm inherits the advantages of the well-known FastICA algorithm of ICA, which is very simple, converges fast, and does not need to choose any learning step sizes. Numerical experiments on electrocardiogram (ECG) data indicate its better performance. © 2012 IEEE. |
| Language: | 英语
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| Content Type: | 会议论文
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| URI: | http://ir.iscas.ac.cn/handle/311060/15952
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| Appears in Collections: | 软件所图书馆_会议论文
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| Recommended Citation: | |
Zhang Hongjuan,Wu Zikai,Ding Shuxue,et al. a fixed-point blind source extraction algorithm and its application to ecg data analysis[C]. 见:2012 IEEE 6th International Conference on Systems Biology, ISB 2012. Xi'an, China. August 18, 2012 - August 20, 2012.
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