| Project/Area Number |
15K16076
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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 |
Kansei informatics
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| Research Institution | The University of Tokyo (2017)
Kyoto University (2015-2016) |
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Principal Investigator |
Nakajima Kohei 東京大学, 大学院情報理工学系研究科, 特任准教授 (10740251)
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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: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2015: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | レザバー計算 / リカレントニューラルネットワーク / 非線形力学系 / ファラデー波 / レザバーコンピューティング / 機械学習 / ニューラルネットワーク / 大自由度力学系 / カオス / ソフトマテリアル |
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| Outline of Final Research Achievements |
When a fluid layer with a free surface is subjected to vertical oscillation, Faraday waves can be observed. Due to their dynamic and nonlinear properties, Faraday waves exhibit complex patterns, such as spatiotemporal chaos. This has posed interesting challenges for many years. In this project, we aim to exploit Faraday waves as information-processing substrates based on the framework of reservoir computing. In particular, we show that they can be used to design timers (or timing control), which require a certain amount of memory to recognize time duration. We also aim to characterize the memory capacity of Faraday waves.
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