Presentation 2022-03-28
Analyses on hierarchical networks of reservoir computing to model visual-information processing
Takumi Shinkawa, Hideyuki Katou,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Recently, reservoir computing is expected to have various engineering applications such as real-time learning of time-series data because of its extremely fast learning speed, compared with the other types of recurrent neural networks. In this study, we attempted to model brain functions, especially visual-information processing, using the reservoir computing. As a first step, we constructed a reservoir computing system with a hierarchical structure and evaluated its functions in the visual-information processing.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) reservoir computing / visual-information processing / hierarchical structure
Paper # MSS2021-59,NLP2021-130
Date of Issue 2022-03-21 (MSS, NLP)

Conference Information
Committee MSS / NLP
Conference Date 2022/3/28(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) MSS, NLP, Work In Progress (MSS only), and etc.
Chair Atsuo Ozaki(Osaka Inst. of Tech.) / Takuji Kosaka(Chukyo Univ.)
Vice Chair Shingo Yamaguchi(Yamaguchi Univ.) / Akio Tsuneda(Kumamoto Univ.)
Secretary Shingo Yamaguchi(Hokkaido Univ.) / Akio Tsuneda(NEC)
Assistant Masato Shirai(Shimane Univ.) / Hideyuki Kato(Oita Univ.) / Yuichi Yokoi(Nagasaki Univ.)

Paper Information
Registration To Technical Committee on Mathematical Systems Science and its Applications / Technical Committee on Nonlinear Problems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Analyses on hierarchical networks of reservoir computing to model visual-information processing
Sub Title (in English)
Keyword(1) reservoir computing
Keyword(2) visual-information processing
Keyword(3) hierarchical structure
1st Author's Name Takumi Shinkawa
1st Author's Affiliation Oita University(Oita Univ)
2nd Author's Name Hideyuki Katou
2nd Author's Affiliation Oita University(Oita Univ)
Date 2022-03-28
Paper # MSS2021-59,NLP2021-130
Volume (vol) vol.121
Number (no) MSS-443,NLP-444
Page pp.pp.23-28(MSS), pp.23-28(NLP),
#Pages 6
Date of Issue 2022-03-21 (MSS, NLP)