Establishing Innovative Machine Learning Mechanism by Cerebellar Spiking Neural Networks
| Project/Area Number |
15K21471
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Soft computing
Intelligent informatics
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| Research Institution | Chiba Institute of Technology (2017)
Fukui University of Technology (2015-2016) |
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Principal Investigator |
Nobukawa Sou 千葉工業大学, 情報科学部, 准教授 (70724558)
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| Research Collaborator |
Nishimura Haruhiko 兵庫県立大学, 大学院・応用情報科学研究科, 教授
Yamanishi Teruya 福井工業大学, 環境情報科学部・経営情報学科, 教授
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | スパイキングニューラルネットワーク / カオス / カオス共鳴 / 小脳 / 下オリーブ核 / 小脳運動学習機構 / 状態跳躍 / 信号応答 / スパイキングニューロンモデル / 下オリーブ / ニューラルネットワーク |
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| Outline of Final Research Achievements |
It is well known that conventional machine learning methods cannot be adopted against dynamically changing systems, adequately. Wile, we have attempted to establish innovative machine learning mechanism, which can be adopted to such systems, by cerebellar spiking neural networks. As the results, we have constructed the spiking neuron models and their networks corresponding to physiological cerebellar learning system. This cerebellar spiking neural network induces the chaotic resonance that enhances the learning ability.
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Report
(4 results)
Research Products
(22 results)
