Critical Reviews™ in Biomedical Engineering

ISSN for PRINT: 0278-940X

For Online Access

Best Paper Award Selection - Editorial Board Site

2000, Volume28

Issue 3&4

328 pages

Issue price - $532.00

Udantha R. Abeyratne
School of Electrical and Electronics Engineering and Biomedical Engineering Research Center, Nanyang Technological University, Nanyang Avenue, Singapore 639798

Ang Kian Tun
School of Electrical and Electronics Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798

Nah Teck Lye
School of Electrical and Electronics Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798

Zhang Guanglan
School of Electrical and Electronics Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798

P. Saratchandran
School of Electrical and Electronics Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798

The backpropagation neural network methods have been proposed recently to solve the inverse problem in quantitative electrophysiology. A major advantage of the technique is that once a neural network is trained, it no longer requires iterations or access to sophisticated computations. We propose to use RBF networks for source localization in the brain, and systematically compare their performance to those of Levenberg-Marquardt (LM) algorithms. We show the use of two types of Radial Basis Function Networks (RBF) network: a classic network with fixed number of hidden layer neurons and an improved network. Minimal Resource Allocation Network (MRAN), recently proposed by one of the authors, capable for dynamically configuring its structure so as to obtain a compact topology to match the data presented to it.

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