Learning Capability of T-Model Neural Network
Summary :
We introduce a novel neural network called the T-Model and investigates the learning ability of the T-Model neural network. A learning algorithm based on the least mean square (LMS) algorithm is used to train the T-Model and produces a very good result for the T-Model network. We present simulation results on several practical problems to illustrate the efficiency of the learning techniques. As a result, the T-Model network learns successfully, but the Hopfield model fails to and the T-Model learns much more effectively and more quickly than a multi-layer network.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E75-A No.7 pp.931-936
- Publication Date
- 1992/07/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Neural Networks
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Keyword
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Okihiko ISHIZUKA, Zheng TANG, Tetsuya INOUE, Hiroki MATSUMOTO, "Learning Capability of T-Model Neural Network" in IEICE TRANSACTIONS on Fundamentals,
vol. E75-A, no. 7, pp. 931-936, July 1992, doi: .
Abstract: We introduce a novel neural network called the T-Model and investigates the learning ability of the T-Model neural network. A learning algorithm based on the least mean square (LMS) algorithm is used to train the T-Model and produces a very good result for the T-Model network. We present simulation results on several practical problems to illustrate the efficiency of the learning techniques. As a result, the T-Model network learns successfully, but the Hopfield model fails to and the T-Model learns much more effectively and more quickly than a multi-layer network.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e75-a_7_931/_p
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@ARTICLE{e75-a_7_931,
author={Okihiko ISHIZUKA, Zheng TANG, Tetsuya INOUE, Hiroki MATSUMOTO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Learning Capability of T-Model Neural Network},
year={1992},
volume={E75-A},
number={7},
pages={931-936},
abstract={We introduce a novel neural network called the T-Model and investigates the learning ability of the T-Model neural network. A learning algorithm based on the least mean square (LMS) algorithm is used to train the T-Model and produces a very good result for the T-Model network. We present simulation results on several practical problems to illustrate the efficiency of the learning techniques. As a result, the T-Model network learns successfully, but the Hopfield model fails to and the T-Model learns much more effectively and more quickly than a multi-layer network.},
keywords={},
doi={},
ISSN={},
month={July},}
Copy
TY - JOUR
TI - Learning Capability of T-Model Neural Network
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 931
EP - 936
AU - Okihiko ISHIZUKA
AU - Zheng TANG
AU - Tetsuya INOUE
AU - Hiroki MATSUMOTO
PY - 1992
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E75-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 1992
AB - We introduce a novel neural network called the T-Model and investigates the learning ability of the T-Model neural network. A learning algorithm based on the least mean square (LMS) algorithm is used to train the T-Model and produces a very good result for the T-Model network. We present simulation results on several practical problems to illustrate the efficiency of the learning techniques. As a result, the T-Model network learns successfully, but the Hopfield model fails to and the T-Model learns much more effectively and more quickly than a multi-layer network.
ER -
English
