Wan Ishak, Wan Hussain and Siraj, Fadzilah and Othman, Abu Talib (2003) A framework for multi-backpropagation. Analisis, 10 (1). pp. 59-68. ISSN 0127-8983

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Abstract

Backpropagation algorithm is one of the most popular learning algorithms in the Neural Network. It has been successfully implemented in many applications. However, training Neural Networks involve a large amount of data. Therefore, training the network is time consuming as each training session requires several epochs, which usually takes smeral seconds or even minutes.This paper proposes a multi-backpropagation approach to minimize the complexity of the network. The approach does not require an alteration of the algorithm. Instead, the large network is split into several smaller networks. An integrating network is then constructed to integrate the output from the smaller networks.

Item Type:	Article
Uncontrolled Keywords:	neural network, backpropagation network, multi backpropagation network
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	College of Arts and Sciences
Depositing User:	Prof Madya Fadzilah Siraj
Date Deposited:	04 Jul 2010 02:06
Last Modified:	04 Jul 2010 02:06
URI:	https://repo.uum.edu.my/id/eprint/94

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