Citation
Loo, , CK and Rao, , MVC and Lim, , WS (2004) Classifiers for sonar target differentiation. KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 2, PROCEEDINGS , 3214 . pp. 305-311. ISSN 0302-9743 Full text not available from this repository.Abstract
In this paper, the processing of sonar signals has been carried out using Minimal Resource Allocation Network (MRAN), Probabilistic Neural Network (PNN) and Fuzzy Artmap (FAM) in differentiation of commonly encountered features in indoor environments. The stability-plasticity behaviors of all three networks have been investigated. The experimental result shows that MRAN possesses lower network complexity but experiences higher plasticity in comparison to PNN and FAM. The study also shows that MRAN performance is superior in terms of on-line learning than PNN and FAM.
Item Type: | Article |
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Subjects: | Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science |
Divisions: | Faculty of Engineering and Technology (FET) |
Depositing User: | Ms Rosnani Abd Wahab |
Date Deposited: | 22 Aug 2011 02:40 |
Last Modified: | 22 Aug 2011 02:40 |
URII: | http://shdl.mmu.edu.my/id/eprint/2499 |
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