| Project/Area Number |
16K16130
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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
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| Research Institution | Ube National College of Technology |
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Principal Investigator |
matsuzaka kenji 宇部工業高等専門学校, 制御情報工学科, 准教授 (00755879)
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| Project Period (FY) |
2016-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2018: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 結合位相振動子系 / ニューラルネットワーク / 電子回路 / 集積回路 / 超大規模脳型回路 / 発火周期保障 / パルス結合位相振動子 / 大規模集積 / アナログ電子回路 |
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| Outline of Final Research Achievements |
In this research, I have developed a pulse-coupled phase oscillator model with complementing firing-period and its CMOS circuit that is robust against variations in between oscillators for VLSI implementation of brain-like intelligent information processing. As a result of verifying a large-scale oscillator network by numerical simulation, it was found that the developed model can eliminate the variation between oscillator units caused by the large-scale integrated circuit. The proposed model/circuit enables the realization of brain-like hardware that executes high-speed and high-efficiency spike-based computation based on the neural network model. By using this proposed model, it is expected that a processor with higher computational efficiency than the current CMOS digital technology will be developed.
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| Academic Significance and Societal Importance of the Research Achievements |
振動子間の動作ばらつきに頑健な発火周期保障型パルス結合位相振動子系モデルおよびそれを実現する回路によって，大規模な振動子ネットワークを回路化するときに生じる問題を解決することができる．これにより，今後，脳の神経細胞モデルに学んだ高速かつ高効率なスパイクベース演算を実行する脳型ハードウェアの実現が可能となり，現在のコンピュータ技術・演算方式とは全く異なる構造をもち，演算効率をはるかに上回るプロセッサが開発できると期待される．
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