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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2006
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| Subjects: | |
| Online Access: | http://shdl.mmu.edu.my/2003/ http://shdl.mmu.edu.my/2003/1/1350.pdf |
| _version_ | 1848789936797384704 |
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| author | Loo, Chu Kiong Law, Augustine Lim, W. S. Rao, M. V. C. |
| author_facet | Loo, Chu Kiong Law, Augustine Lim, W. S. Rao, M. V. C. |
| author_sort | Loo, Chu Kiong |
| building | MMU Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T18:04:39Z |
| format | Article |
| id | mmu-2003 |
| institution | Multimedia University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:04:39Z |
| publishDate | 2006 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-20032011-08-10T05:31:36Z http://shdl.mmu.edu.my/2003/ Probabilistic ensemble simplified fuzzy ARTMAP for sonar target differentiation Loo, Chu Kiong Law, Augustine Lim, W. S. Rao, M. V. C. QA75.5-76.95 Electronic computers. Computer science 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. 2006-03 Article NonPeerReviewed application/pdf en http://shdl.mmu.edu.my/2003/1/1350.pdf Loo, Chu Kiong and Law, Augustine 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://dx.doi.org/10.1007/s00521-005-0010-1 doi:10.1007/s00521-005-0010-1 doi:10.1007/s00521-005-0010-1 |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Loo, Chu Kiong Law, Augustine 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 | QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/2003/ http://shdl.mmu.edu.my/2003/ http://shdl.mmu.edu.my/2003/ http://shdl.mmu.edu.my/2003/1/1350.pdf |