- Abstract:
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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...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted manuscript
- Files:
-
-
(pdf, 3.4mb)
-
- Publisher copy:
- 10.1016/j.ymssp.2017.09.041
-
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- 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:
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1096-1216
- ISSN:
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0888-3270
- Pubs id:
-
pubs:746931
- URN:
-
uri:868a1ff8-9ffd-4512-a8ad-24e6ac41ef7c
- UUID:
-
uuid:868a1ff8-9ffd-4512-a8ad-24e6ac41ef7c
- Local pid:
- pubs:746931
- Copyright holder:
- Elsevier Ltd.
- Copyright date:
- 2017
- Notes:
- © 2017 Elsevier Ltd. All rights reserved. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.ymssp.2017.09.041
Journal article
Component isolation for multi-component signal analysis using a non-parametric gaussian latent feature model
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K.C. Wong Education Foundation
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Royal Academy of Engineering
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