Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals

Biomedical signals are non-stationary and a research topic of practical interest as the signal has time varying statistics. The problem of time varying is usually circumvented by assuming local stationary over a short time interval, where stationary techniques are applied. However, features extract...

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Main Authors:	Najeeb, Athaur Rahman, Salami, Momoh Jimoh Emiyoka, Gunawan, Teddy Surya, Aibinu, Abiodun Musa
Format:	Article
Language:	English
Published:	International Journal of Signal Processing Systems 2016
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://irep.iium.edu.my/45583/ http://irep.iium.edu.my/45583/ http://irep.iium.edu.my/45583/ http://irep.iium.edu.my/45583/6/45583_Review%20of%20parameter%20estimation%20techniques_text.pdf

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recordtype	eprints
spelling	iium-455832017-06-05T01:49:10Z http://irep.iium.edu.my/45583/ Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals Najeeb, Athaur Rahman Salami, Momoh Jimoh Emiyoka Gunawan, Teddy Surya Aibinu, Abiodun Musa QA75 Electronic computers. Computer science Biomedical signals are non-stationary and a research topic of practical interest as the signal has time varying statistics. The problem of time varying is usually circumvented by assuming local stationary over a short time interval, where stationary techniques are applied. However, features extracted from these methods are not always suitable and methods for non-stationary process are needed. Time varying signals are more accurately represented by time frequency methods and received most attention recently. Among the time frequency methods, parametric modeling such as TVAR has been promising over non-parametric methods with improved resolutions and able to trace strong non-stationary signal. Despite the success of TVAR in various applications it has drawbacks. This paper presents an extensive review on TVAR modelling techniques. Different approaches for TVAR modeling is presented and outlined. Principles, advantages, disadvantages of those techniques are presented concisely. And finally a new direction has been suggested briefly. International Journal of Signal Processing Systems 2016-06 Article PeerReviewed application/pdf en http://irep.iium.edu.my/45583/6/45583_Review%20of%20parameter%20estimation%20techniques_text.pdf Najeeb, Athaur Rahman and Salami, Momoh Jimoh Emiyoka and Gunawan, Teddy Surya and Aibinu, Abiodun Musa (2016) Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals. International Journal of Signal Processing Systems, 4 (3). pp. 220-225. ISSN 2315-4535 http://www.ijsps.com/uploadfile/2016/0628/20160628103045310.pdf doi: 10.18178/ijsps.4.3.220-225
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Najeeb, Athaur Rahman Salami, Momoh Jimoh Emiyoka Gunawan, Teddy Surya Aibinu, Abiodun Musa Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals
description	Biomedical signals are non-stationary and a research topic of practical interest as the signal has time varying statistics. The problem of time varying is usually circumvented by assuming local stationary over a short time interval, where stationary techniques are applied. However, features extracted from these methods are not always suitable and methods for non-stationary process are needed. Time varying signals are more accurately represented by time frequency methods and received most attention recently. Among the time frequency methods, parametric modeling such as TVAR has been promising over non-parametric methods with improved resolutions and able to trace strong non-stationary signal. Despite the success of TVAR in various applications it has drawbacks. This paper presents an extensive review on TVAR modelling techniques. Different approaches for TVAR modeling is presented and outlined. Principles, advantages, disadvantages of those techniques are presented concisely. And finally a new direction has been suggested briefly.
format	Article
author	Najeeb, Athaur Rahman Salami, Momoh Jimoh Emiyoka Gunawan, Teddy Surya Aibinu, Abiodun Musa
author_facet	Najeeb, Athaur Rahman Salami, Momoh Jimoh Emiyoka Gunawan, Teddy Surya Aibinu, Abiodun Musa
author_sort	Najeeb, Athaur Rahman
title	Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals
title_short	Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals
title_full	Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals
title_fullStr	Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals
title_full_unstemmed	Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals
title_sort	review of parameter estimation techniques for time-varying autoregressive models of biomedical signals
publisher	International Journal of Signal Processing Systems
publishDate	2016
url	http://irep.iium.edu.my/45583/ http://irep.iium.edu.my/45583/ http://irep.iium.edu.my/45583/ http://irep.iium.edu.my/45583/6/45583_Review%20of%20parameter%20estimation%20techniques_text.pdf
first_indexed	2023-09-18T21:04:50Z
last_indexed	2023-09-18T21:04:50Z
_version_	1777410863863431168

Review of parameter estimation techniques for time-varying autoregressive models of biomedical signals

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