Matching and fusing signal-estimation errors for similarity-based pattern classification
Pham, Tuan D. (2007) Matching and fusing signal-estimation errors for similarity-based pattern classification. WSEAS Transactions on Systems, 6 (1). pp. 125-132.
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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.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||linear prediction; error matching; similarity measure, information fusion; classification|
Reproduced with permission from World Scientific and Engineering Academy and Society (WSEAS).
|Date Deposited:||28 Sep 2009 04:11|
|FoR Codes:||10 TECHNOLOGY > 1099 Other Technology > 109999 Technology not elsewhere classified @ 34%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing @ 33%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080108 Neural, Evolutionary and Fuzzy Computation @ 33%
|SEO Codes:||92 HEALTH > 9202 Health and Support Services > 920203 Diagnostic Methods @ 100%|
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