The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of APPLIED MATHEMATICS AND INFORMATICS
Transactions ID Number: 19-528
Full Name: Corina Sararu
Position: Assistant Professor
Age: ON
Sex: Female
Address: Pitesti, Arges, Str. D. Cantemir, No. 2, Bl. P8, Ap. 14, Sc. A
Country: ROMANIA
Tel: 0040720021161
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E-mail address: corina_sararu@yahoo.com
Other E-mails: corina.sararu@upit.ro
Title of the Paper: Independent Component Analysis and Complex Wavelet Decomposition for Classifying Medical Data
Authors as they appear in the Paper: Corina Sararu, Luminita State, Maria Miroiu
Email addresses of all the authors: corina.sararu@upit.ro,lstate@clicknet.ro,maria.miroiu@upit.ro
Number of paper pages: 8
Abstract: In this article, we describe a new classification methodology based on the use of Independent Component Analysis and Wavelet decomposition (ICAW) techniques. An ensemble system of classifiers is built such that each classifier independently decides the assignation of the test examples on several representations resulted by taking projections computed by wavelets and Independent Component Analysis (ICA). The representations used by the individual classifiers are obtained by taking the real and imaginary part of the wavelet decompositions,as well as the magnitude and phase. The decision of the ensemble system is based on several types of voting rules (such as the majority voting rule or a weighted voting rule). The experimental results presented in the paper show that the proposed ensemble systems of classifiers provide higher accuracy in the particular problem of classifying biomedical data.
Keywords: Independent components analysis, Wavelet decomposition, Pattern recognition, Signal processing
EXTENSION of the file: .pdf
Special (Invited) Session: A New Heuristic Classifier Design Based on Independent Component Analysis and Wavelet Methods
Organizer of the Session: 201-141
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