Remarks on an Immune-Feedback-Based Learning of Neural Networks
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- Yamada Takayuki
- NTT
Bibliographic Information
- Other Title
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- ニューラルネットワークの免疫制御型学習に関する一考察
- ニューラル ネットワーク ノ メンエキ セイギョガタ ガクシュウ ニ カンスル イチ コウサツ
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Abstract
As an engineering application of a biological immune system, an immune feedback control law featuring rapid response to foreign materials and quick stabilization of the immune system is applied to controlling the learning of multi-layer neural networks. Applying the immune feedback control law to the generalized δ-rule, the immune-feedback-based learning rule is derived. The stability condition of the proposed learning rule for the 2-layer neural networks is analytically described. To investigate the feasibility of the proposed learning rule to the multi-layer neural networks, simulation studies of identifying nonlinear functions using the 4-layer neural networks and the sandglass-type neural networks are carried out. Simulation results show both the effectiveness and characteristics of the immune feedback-based learning rule.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 119 (8-9), 935-941, 1999
The Institute of Electrical Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390001204611715968
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- NII Article ID
- 130006846023
- 10004630099
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 4816283
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed