Performance of Affordable Neural Network for Back Propagation Learning
Summary :
Cell assembly is one of explanations of information processing in the brain, in which an information is represented by a firing space pattern of a group of plural neurons. On the other hand, effectiveness of neural network has been confirmed in pattern recognition, system control, signal processing, and so on, since the back propagation learning was proposed. In this study, we propose a new network structure with affordable neurons in the hidden layer of the feedforward neural network. Computer simulated results show that the proposed network exhibits a good performance for the back propagation learning. Furthermore, we confirm the proposed network has a good generalization ability.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E89-A No.9 pp.2374-2380
- Publication Date
- 2006/09/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e89-a.9.2374
- Type of Manuscript
- PAPER
- Category
- Nonlinear Problems
Authors
Keyword
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Yoko UWATE, Yoshifumi NISHIO, "Performance of Affordable Neural Network for Back Propagation Learning" in IEICE TRANSACTIONS on Fundamentals,
vol. E89-A, no. 9, pp. 2374-2380, September 2006, doi: 10.1093/ietfec/e89-a.9.2374.
Abstract: Cell assembly is one of explanations of information processing in the brain, in which an information is represented by a firing space pattern of a group of plural neurons. On the other hand, effectiveness of neural network has been confirmed in pattern recognition, system control, signal processing, and so on, since the back propagation learning was proposed. In this study, we propose a new network structure with affordable neurons in the hidden layer of the feedforward neural network. Computer simulated results show that the proposed network exhibits a good performance for the back propagation learning. Furthermore, we confirm the proposed network has a good generalization ability.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e89-a.9.2374/_p
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@ARTICLE{e89-a_9_2374,
author={Yoko UWATE, Yoshifumi NISHIO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Performance of Affordable Neural Network for Back Propagation Learning},
year={2006},
volume={E89-A},
number={9},
pages={2374-2380},
abstract={Cell assembly is one of explanations of information processing in the brain, in which an information is represented by a firing space pattern of a group of plural neurons. On the other hand, effectiveness of neural network has been confirmed in pattern recognition, system control, signal processing, and so on, since the back propagation learning was proposed. In this study, we propose a new network structure with affordable neurons in the hidden layer of the feedforward neural network. Computer simulated results show that the proposed network exhibits a good performance for the back propagation learning. Furthermore, we confirm the proposed network has a good generalization ability.},
keywords={},
doi={10.1093/ietfec/e89-a.9.2374},
ISSN={1745-1337},
month={September},}
Copy
TY - JOUR
TI - Performance of Affordable Neural Network for Back Propagation Learning
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2374
EP - 2380
AU - Yoko UWATE
AU - Yoshifumi NISHIO
PY - 2006
DO - 10.1093/ietfec/e89-a.9.2374
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E89-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2006
AB - Cell assembly is one of explanations of information processing in the brain, in which an information is represented by a firing space pattern of a group of plural neurons. On the other hand, effectiveness of neural network has been confirmed in pattern recognition, system control, signal processing, and so on, since the back propagation learning was proposed. In this study, we propose a new network structure with affordable neurons in the hidden layer of the feedforward neural network. Computer simulated results show that the proposed network exhibits a good performance for the back propagation learning. Furthermore, we confirm the proposed network has a good generalization ability.
ER -
English
