Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation

This Study investigates the processing of sonar signals with ensemble neural networks for robust recognition of simple objects such as plane, corner and trapezium surface. The ensemble neural networks can differentiate the target objects with high accuracy. The simplified fuzzy ARTMAP (SFAM) and pro...

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Main Authors: Loo, Chu Kiong, Law, A., Lim, W.S., Rao, M.V.C.
Format: Article
Published: Springer Verlag (Germany) 2006
Subjects:
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author Loo, Chu Kiong
Law, A.
Lim, W.S.
Rao, M.V.C.
author_facet Loo, Chu Kiong
Law, A.
Lim, W.S.
Rao, M.V.C.
author_sort Loo, Chu Kiong
collection UM
description This Study investigates the processing of sonar signals with ensemble neural networks for robust recognition of simple objects such as plane, corner and trapezium surface. The ensemble neural networks can differentiate the target objects with high accuracy. The simplified fuzzy ARTMAP (SFAM) and probabilistic ensemble simplified fuzzy ARTMAP (PESFAM) are compared in terms of classification accuracy. The PESFAM implements an accurate and effective probabilistic plurality voting method to combine outputs from multiple SFAM classifiers. Five benchmark data sets have been used to evaluate the applicability of the proposed ensemble SFAM network. The PESFAM achieves good accuracy based on the twofold cross-validation results. In addition, the effectiveness of the proposed ensemble SFAM is delineated in sonar target differentiation. The experiments demonstrate the potential of PESFAM classifiers in offering an optimal solution to the data-ordering problem of SFAM implementation and also as an intelligent classification tool in mobile robot application.
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spelling um.eprints-51752020-01-16T01:53:07Z http://eprints.um.edu.my/5175/ Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation Loo, Chu Kiong Law, A. Lim, W.S. Rao, M.V.C. T Technology (General) This Study investigates the processing of sonar signals with ensemble neural networks for robust recognition of simple objects such as plane, corner and trapezium surface. The ensemble neural networks can differentiate the target objects with high accuracy. The simplified fuzzy ARTMAP (SFAM) and probabilistic ensemble simplified fuzzy ARTMAP (PESFAM) are compared in terms of classification accuracy. The PESFAM implements an accurate and effective probabilistic plurality voting method to combine outputs from multiple SFAM classifiers. Five benchmark data sets have been used to evaluate the applicability of the proposed ensemble SFAM network. The PESFAM achieves good accuracy based on the twofold cross-validation results. In addition, the effectiveness of the proposed ensemble SFAM is delineated in sonar target differentiation. The experiments demonstrate the potential of PESFAM classifiers in offering an optimal solution to the data-ordering problem of SFAM implementation and also as an intelligent classification tool in mobile robot application. Springer Verlag (Germany) 2006 Article PeerReviewed Loo, Chu Kiong and Law, A. and Lim, W.S. and Rao, M.V.C. (2006) Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation. Neural Computing and Applications, 15 (1). pp. 79-90. ISSN 0941-0643, http://download.springer.com/static/pdf/775/art%253A10.1007%252Fs00521-005-0010-1.pdf?auth66=1352708401_338c8b84c0323ac65ee4ad8270b8185f&ext=.pdf
spellingShingle T Technology (General)
Loo, Chu Kiong
Law, A.
Lim, W.S.
Rao, M.V.C.
Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation
title Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation
title_full Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation
title_fullStr Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation
title_full_unstemmed Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation
title_short Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation
title_sort probabilistic ensemble simplified fuzzy artmap for sonar target differentiation
topic T Technology (General)
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AT lawa probabilisticensemblesimplifiedfuzzyartmapforsonartargetdifferentiation
AT limws probabilisticensemblesimplifiedfuzzyartmapforsonartargetdifferentiation
AT raomvc probabilisticensemblesimplifiedfuzzyartmapforsonartargetdifferentiation