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Twofold application of principal component analysis to the signals of impulse breath radar

Twofold application of principal component analysis to the signals of impulse breath radar Using model and real signals, the possibility and appropriateness of low-frequency component (trend) filtering using singular spectrum analysis (SSA) based on principal component analysis is considered. The real signals are represented by human breathing curves obtained after processing of UWB (ultrawideband) impulse signals using the principal component analysis. It has been shown experimentally that the use of the SSA makes it possible to suppress an interfering trend down to 18 dB. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Automatic Control and Computer Sciences Springer Journals

Twofold application of principal component analysis to the signals of impulse breath radar

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Publisher
Springer Journals
Copyright
Copyright © 2013 by Allerton Press, Inc.
Subject
Computer Science; Control Structures and Microprogramming
ISSN
0146-4116
eISSN
1558-108X
DOI
10.3103/S0146411613060059
Publisher site
See Article on Publisher Site

Abstract

Using model and real signals, the possibility and appropriateness of low-frequency component (trend) filtering using singular spectrum analysis (SSA) based on principal component analysis is considered. The real signals are represented by human breathing curves obtained after processing of UWB (ultrawideband) impulse signals using the principal component analysis. It has been shown experimentally that the use of the SSA makes it possible to suppress an interfering trend down to 18 dB.

Journal

Automatic Control and Computer Sciences – Springer Journals

Published: Jan 14, 2014

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    Immoreev, I; Tao, T-H
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    Golyandina, N; Znigliavsky, A