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Matching and fusing signal-estimation errors for similarity-based pattern classification
Bioinfonnatics Applications Research Centre/School of Mathematics, Physics, and Infonnation Technology James Cook University Townsville, AUSTRALIA.ORCID iD: 0000-0002-4255-5130
2007 (English)In: WSEAS Transactions on Systems, ISSN 1109-2777, Vol. 6, no 1, 125-132 p.Article in journal (Refereed) PublishedText
Abstract [en]

Error estimation using different optimal models for signal processing has been an active research field in data analysis such as speech recognition, image analysis, geophysics, and earth science. A popular direction of research in pattern classification is to develop computational models for comparing objects being either abstract or physical based on some measure of similarity or dissimilarity. This paper explores some linear-prediction models for deriving signal estimation errors and their fusion for similarity-based pattern classification.

Place, publisher, year, edition, pages
2007. Vol. 6, no 1, 125-132 p.
Keyword [en]
linear prediction; error matching; similarity measure, information fusion; classification
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-125034OAI: diva2:902759
Available from: 2016-02-12 Created: 2016-02-12 Last updated: 2016-02-24

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Pham, Tuan D
Control Engineering

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