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

Hybrid Source Extraction Techniques for Periodic Signals

Authors
Haining Jiang, Yongjian Zhao
Corresponding Author
Haining Jiang
Available Online July 2015.
DOI
10.2991/icimm-15.2015.81How to use a DOI?
Keywords
Structure; Feature; Period; Mixture; Signal
Abstract

Many natural signals, such as speech signal and biomedical signal, have significant temporal structure. This work is motivated that the majority of physiological signal mixtures show some degree of periodicity and statistical nonstationarity. In fact, the nonstationarity has testified itself to be variations in period as a function of time. By exploiting the linear autocorrelation features of desired signal, a hybrid method is proposed for source signal extraction. Extensive computer simulations demonstrate the utility of the introduced techniques.

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-15.2015.81How 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

TY  - CONF
AU  - Haining Jiang
AU  - Yongjian Zhao
PY  - 2015/07
DA  - 2015/07
TI  - Hybrid Source Extraction Techniques for Periodic Signals
BT  - Proceedings of the 5th International Conference on Information Engineering for Mechanics and Materials
PB  - Atlantis Press
SP  - 429
EP  - 433
SN  - 2352-5401
UR  - https://doi.org/10.2991/icimm-15.2015.81
DO  - 10.2991/icimm-15.2015.81
ID  - Jiang2015/07
ER  -