Independent Component Analysis Based on Information Bottleneck
The paper is mainly used to provide the equivalence of two algorithms of independent component analysis (ICA) based on the information bottleneck (IB). In the viewpoint of information theory, we attempt to explain the two classical algorithms of ICA by information bottleneck. Furthermore, via the nu...
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Series: | Abstract and Applied Analysis |
Online Access: | http://dx.doi.org/10.1155/2015/386201 |
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doaj-fab793f5eac44e3c8a3636d7d337c9d52020-11-24T23:14:27ZengHindawi LimitedAbstract and Applied Analysis1085-33751687-04092015-01-01201510.1155/2015/386201386201Independent Component Analysis Based on Information BottleneckQiao Ke0Jiangshe Zhang1H. M. Srivastava2Wei Wei3Guang-Sheng Chen4School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, ChinaDepartment of Mathematics and Statistics, University of Victoria, Victoria, BC, V8W 3R4, CanadaSchool of Computer Science and Engineering, Xi’an University of Technology, Shaanxi Key Laboratory for Network Computing and Security Technology, Xi’an 710048, ChinaDepartment of Construction and Information Engineering, Guangxi Modern Vocational Technology College, Hechi, Guangxi 547000, ChinaThe paper is mainly used to provide the equivalence of two algorithms of independent component analysis (ICA) based on the information bottleneck (IB). In the viewpoint of information theory, we attempt to explain the two classical algorithms of ICA by information bottleneck. Furthermore, via the numerical experiments with the synthetic data, sonic data, and image, ICA is proved to be an edificatory way to solve BSS successfully relying on the information theory. Finally, two realistic numerical experiments are conducted via FastICA in order to illustrate the efficiency and practicality of the algorithm as well as the drawbacks in the process of the recovery images the mixing images.http://dx.doi.org/10.1155/2015/386201 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Qiao Ke Jiangshe Zhang H. M. Srivastava Wei Wei Guang-Sheng Chen |
spellingShingle |
Qiao Ke Jiangshe Zhang H. M. Srivastava Wei Wei Guang-Sheng Chen Independent Component Analysis Based on Information Bottleneck Abstract and Applied Analysis |
author_facet |
Qiao Ke Jiangshe Zhang H. M. Srivastava Wei Wei Guang-Sheng Chen |
author_sort |
Qiao Ke |
title |
Independent Component Analysis Based on Information Bottleneck |
title_short |
Independent Component Analysis Based on Information Bottleneck |
title_full |
Independent Component Analysis Based on Information Bottleneck |
title_fullStr |
Independent Component Analysis Based on Information Bottleneck |
title_full_unstemmed |
Independent Component Analysis Based on Information Bottleneck |
title_sort |
independent component analysis based on information bottleneck |
publisher |
Hindawi Limited |
series |
Abstract and Applied Analysis |
issn |
1085-3375 1687-0409 |
publishDate |
2015-01-01 |
description |
The paper is mainly used to provide the equivalence of two algorithms of independent component analysis (ICA) based on the information bottleneck (IB). In the viewpoint of information theory, we attempt to explain the two classical algorithms of ICA by information bottleneck. Furthermore, via the numerical experiments with the synthetic data, sonic data, and image, ICA is proved to be an edificatory way to solve BSS successfully relying on the information theory. Finally, two realistic numerical experiments are conducted via FastICA in order to illustrate the efficiency and practicality of the algorithm as well as the drawbacks in the process of the recovery images the mixing images. |
url |
http://dx.doi.org/10.1155/2015/386201 |
work_keys_str_mv |
AT qiaoke independentcomponentanalysisbasedoninformationbottleneck AT jiangshezhang independentcomponentanalysisbasedoninformationbottleneck AT hmsrivastava independentcomponentanalysisbasedoninformationbottleneck AT weiwei independentcomponentanalysisbasedoninformationbottleneck AT guangshengchen independentcomponentanalysisbasedoninformationbottleneck |
_version_ |
1725594271898140672 |