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Journal article

Component isolation for multi-component signal analysis using a non-parametric gaussian latent feature model

Abstract:

A challenge in analysing non-stationary multi-component signals is to isolate nonlinearly time-varying signals especially when they are overlapped in time and frequency plane. In this paper, a framework integrating time-frequency analysis-based demodulation and a non-parametric Gaussian latent feature model is proposed to isolate and recover components of such signals. The former aims to remove high-order frequency modulation (FM) such that the latter is able to infer demodulated components w...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted manuscript

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Publisher copy:
10.1016/j.ymssp.2017.09.041

Authors


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ORCID:
0000-0002-2095-7075
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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering Science
Oxford college:
Balliol College
K.C. Wong Education Foundation More from this funder
Royal Academy of Engineering More from this funder
Publisher:
Elsevier Publisher's website
Journal:
Mechanical Systems and Signal Processing Journal website
Volume:
103
Pages:
368-380
Publication date:
2017-11-03
Acceptance date:
2017-09-29
DOI:
EISSN:
1096-1216
ISSN:
0888-3270
Pubs id:
pubs:746931
URN:
uri:868a1ff8-9ffd-4512-a8ad-24e6ac41ef7c
UUID:
uuid:868a1ff8-9ffd-4512-a8ad-24e6ac41ef7c
Local pid:
pubs:746931

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