Hybrid Source Extraction Techniques for Periodic Signals

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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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  -