DSpace university logo mark
Advanced Search
Japanese | English 

NAOSITE : Nagasaki University's Academic Output SITE > Faculty of Engineering > Bulletin > Reports of the Faculty of Engineering, Nagasaki University > Volume 26, No. 46 >

情報量最大化学習を用いたニューラルネットワークの特性


File Description SizeFormat
KJ00004723854.pdf604.92 kBAdobe PDFView/Open

Title: 情報量最大化学習を用いたニューラルネットワークの特性
Other Titles: Features of Neural Networks Using Learning Algorithm Based on Maximizing Amount of Information
Authors: 姉川, 正紀 / 志久, 修 / 中村, 千秋 / 中村, 彰
Authors (alternative): Anegawa, Masanori / Shiku, Osamu / Nakamura, Chiaki / Nakamura, Akira
Issue Date: Jan-1996
Citation: 長崎大学工学部研究報告 Vol.26(46) p. 31-37, 1996
Abstract: A new learning algorithm based on the amount of information is proposed in this paper. A neuron pool (a group of neurons) is adopted as a basic information processing unit and the neuron-pools-network is self organized according to the proposed rule invented imitating 'Homeostasis' (maintain the constancy of life) of a living body. Learning is carried out in such a way that the amount of information of each neuron pool brings to maximum. Simulation was carried out using the simple neuron-pools-networks that neuron pools are alined in one dimension and multiple layers. The results show that it behaves similar to a living body and has pattern recognition ability to some extent.
URI: http://hdl.handle.net/10069/14963
ISSN: 02860902
Type: Departmental Bulletin Paper
Appears in Collections:Volume 26, No. 46

Citable URI : http://hdl.handle.net/10069/14963

All items in NAOSITE are protected by copyright, with all rights reserved.

 

Valid XHTML 1.0! Copyright © 2006-2015 Nagasaki University Library - Feedback Powerd by DSpace