Classifiers for sonar target differentiation

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
Subjects: Q Science > QA Mathematics > 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
URI: http://shdl.mmu.edu.my/id/eprint/2499

Actions (login required)

View Item View Item