Proceedings of the 5th International Conference on Information Engineering for Mechanics and Materials

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Hybrid Techniques for Blind Source Separation

Authors
Haining Jiang, Yongjian Zhao
Corresponding Author
Haining Jiang
Available Online July 2015.
DOI
10.2991/icimm-15.2015.80How to use a DOI?
Keywords
Source; Separation; Extraction; Distribution; kurtosis
Abstract

This paper proposes a parametric density model under a maximum likelihood framework. One may set different exponential parameters, based on the kurtosis properties of the desired signal, to match different possible signal distributions. In contrast to traditional techniques, the proposed signal separation method can provide more freedom and low computation load.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 5th International Conference on Information Engineering for Mechanics and Materials
Series
Advances in Engineering Research
Publication Date
July 2015
ISBN
978-94-62520-88-2
ISSN
2352-5401
DOI
10.2991/icimm-15.2015.80How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Haining Jiang
AU  - Yongjian Zhao
PY  - 2015/07
DA  - 2015/07
TI  - Hybrid Techniques for Blind Source Separation
BT  - Proceedings of the 5th International Conference on Information Engineering for Mechanics and Materials
PB  - Atlantis Press
SP  - 424
EP  - 428
SN  - 2352-5401
UR  - https://doi.org/10.2991/icimm-15.2015.80
DO  - 10.2991/icimm-15.2015.80
ID  - Jiang2015/07
ER  -