Entropy learning in neural network

Geok, See Ng and Shi, Daming and Abdul Rahman, Abdul Wahab and Singh, H. (2003) Entropy learning in neural network. ASEAN Journal for Science and Technology Development, 20 (3&4). pp. 307-322. ISSN 0217-5460 (P), 0976-3376 (O)

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Abstract

In this paper, entropy term is used in the learning phase of a neural network. As learning progresses, more hidden nodes get into saturation. The early creation of such hidden nodes may impair generalisation. Hence entropy approach is proposed to dampen the early creation of such nodes. The entropy learning also helps to increase the importance of relevant nodes while dampening the less important nodes. At the end of learning, the less important nodes can then be eliminated to reduce the memory requirements of the neural network.

Item Type:	Article (Journal)
Additional Information:	6145/38199
Uncontrolled Keywords:	entropy learning, neural network
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Ahmad Nazreen Mohd Shamsuri (PT)
Date Deposited:	12 Sep 2014 09:42
Last Modified:	12 Sep 2014 09:42
URI:	http://irep.iium.edu.my/id/eprint/38199

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