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FS Focused Session "AI Electronics" » FS.1 Focused Session "AI Electronics"

[23p-M206-1~13] FS.1 Focused Session "AI Electronics"

Fri. Sep 23, 2022 1:30 PM - 5:00 PM M206 (Multimedia Research Hall)

Shinichi Takagi(Univ. of Tokyo), Norio Sato(NTT), Yoshihiko Horio(東北大)

△：Presentation by Applicant for JSAP Young Scientists Presentation Award
▲：English Presentation
▼：Both of Above
No Mark：None of Above

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1:30 PM - 1:45 PM

[23p-M206-1] [Young Scientist Presentation Award Speech] Reservoir computing using ferroelectric MFM capacitors

〇Eishin Nako¹, Kasidit Toprasertpong¹, Zeyu Wang¹, Ryosho Nakane¹, Mitsuru Takenaka¹, Shinichi Takagi¹ (1.Univ. Tokyo)

1:45 PM - 2:00 PM

△ [23p-M206-2] Optical skin soft interface based on soft material and machine learning

〇(M1C)Kei Kitagawa¹, Koyo Sagehashi¹, Tomoaki Niiyama², Satoshi Sunada^2,3 (1.Kanazawa Univ., 2.Kanazawa Univ. S and E, 3.JST PRESTO)

2:00 PM - 2:15 PM

△ [23p-M206-3] Experimental Demonstration of Reservoir Computing wth Nonlinear-interfered Spin Waves

〇(P)Wataru Namiki¹, Daiki Nishioka^1,2, Yu Yamaguchi^1,2, Takashi Tsuchiya¹, Tohru Higuchi², Kazuya Terabe¹ (1.NIMS, 2.Tokyo Univ. of Sci.)

2:15 PM - 2:30 PM

[23p-M206-4] A Ag₂S Island Network Reservoir that works with Optical Signal Inputs

〇Yosuke Shimizu¹, Kazuki Minegishi¹, Tsuyoshi Hasegawa¹ (1.Waseda Univ.)

2:30 PM - 2:45 PM

[23p-M206-5] Frequency Dependence of Operations in an Ag₂S Island Network Reservoir

〇Kazuki Minegishi¹, Yosuke Shimizu¹, Tsuyoshi Hasegawa¹ (1.Waseda Univ.)

2:45 PM - 3:00 PM

△ [23p-M206-6] Reservoir computing utilising photoresponsive properties of ITO/Nb:SrTiO₃ junctions

〇(M1)Yutaro Yamazaki¹, Hiroyuki Kai¹, Kentaro Kinoshita¹ (1.Tokyo Univ. of Sci.)

3:00 PM - 3:15 PM

△ [23p-M206-7] Improvement of Power Saving and Learning Accuracy in Ionic Liquid-based Physical Reservoir Devices by Dehydration of Ionic Liquid

〇Masaharu Yonezawa^1,2, Shima Hisashi², Matsuo Takuma^1,2, Naitoh Yasuhisa², Akinaga Hiroyuki², Itoh Toshiyuki³, Nokami Toshiki⁴, Kobayashi Masakazu^1,5, Kinoshita Kentaro¹ (1.Tokyo Univ. of Sci., 2.AIST, 3.Toyota Physical & Chemical Research Institute, 4.Tottori Univ., 5.NAGASE & CO., LTD.)

3:30 PM - 3:45 PM

[23p-M206-8] Reservoir Computing Approach for Surface Myoelectric Signal Analysis and Voluntary Motion Readout

〇Takato Yoshida¹, Seiya Kasai¹ (1.RCIQE Hokkaido Univ.)

3:45 PM - 4:00 PM

[23p-M206-9] Data augmentation for classification by electrochemical dynamics reservoir

〇Yuki Usami^1,2, Yuichiro Tanaka^1,2, Takumi Kotooka¹, Hakaru Tamukoh^1,2, Hirofumi Tanaka^1,2 (1.Kyushu Inst. Tech. LSSE, 2.Kyushu Inst. Tech. Neumorph Center)

4:00 PM - 4:15 PM

[23p-M206-10] Optimization of the short-term memory characteristics of ionic liquid physical reservoirs by temperature control

〇Asahi Arai¹, Sang-Gyu Koh¹, Taiki Koide¹, Hiroyuki Kai¹, Kentaro Kinoshita¹ (1.Tokyo Univ of Sci.)

4:15 PM - 4:30 PM

[23p-M206-11] Proposal of FeFET reservoir computing with parallel data processing for speech recognition and experimental examination of the performance

〇Eishin Nako¹, Kasidit Toprasertpong¹, Ryosho Nakane¹, Mitsuru Takenaka¹, Shinichi Takagi¹ (1.Univ. Tokyo)

4:30 PM - 4:45 PM

[23p-M206-12] Approaches to enhance the performance of FeFET reservoir computing with parallel data processing for speech recognition

〇Eishin Nako¹, Kasidit Toprasertpong¹, Ryosho Nakane¹, Mitsuru Takenaka¹, Shinichi Takagi¹ (1.Univ. Tokyo)

4:45 PM - 5:00 PM

[23p-M206-13] Physical reservoir computing using multi-terminal carbon nanotube thin film transistors

〇(M1)Takeshi Watanabe¹, Haruki Uchiyama¹, Yutaka Ohno^1,2 (1.Nagoya Univ., 2.IMaSS Nagoya Univ.)

Session information

[23p-M206-1~13] FS.1 Focused Session "AI Electronics"

[23p-M206-1] [Young Scientist Presentation Award Speech] Reservoir computing using ferroelectric MFM capacitors

△ [23p-M206-2] Optical skin soft interface based on soft material and machine learning

△ [23p-M206-3] Experimental Demonstration of Reservoir Computing wth Nonlinear-interfered Spin Waves

[23p-M206-4] A Ag₂S Island Network Reservoir that works with Optical Signal Inputs

[23p-M206-5] Frequency Dependence of Operations in an Ag₂S Island Network Reservoir

△ [23p-M206-6] Reservoir computing utilising photoresponsive properties of ITO/Nb:SrTiO₃ junctions

△ [23p-M206-7] Improvement of Power Saving and Learning Accuracy in Ionic Liquid-based Physical Reservoir Devices by Dehydration of Ionic Liquid

[23p-M206-8] Reservoir Computing Approach for Surface Myoelectric Signal Analysis and Voluntary Motion Readout

[23p-M206-9] Data augmentation for classification by electrochemical dynamics reservoir

[23p-M206-10] Optimization of the short-term memory characteristics of ionic liquid physical reservoirs by temperature control

[23p-M206-11] Proposal of FeFET reservoir computing with parallel data processing for speech recognition and experimental examination of the performance

[23p-M206-12] Approaches to enhance the performance of FeFET reservoir computing with parallel data processing for speech recognition

[23p-M206-13] Physical reservoir computing using multi-terminal carbon nanotube thin film transistors

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Session information

[23p-M206-1~13] FS.1 Focused Session "AI Electronics"

△ [23p-M206-2] Optical skin soft interface based on soft material and machine learning

△ [23p-M206-3] Experimental Demonstration of Reservoir Computing wth Nonlinear-interfered Spin Waves

△ [23p-M206-6] Reservoir computing utilising photoresponsive properties of ITO/Nb:SrTiO3 junctions

△ [23p-M206-7] Improvement of Power Saving and Learning Accuracy in Ionic Liquid-based Physical Reservoir Devices by Dehydration of Ionic Liquid

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△ [23p-M206-6] Reservoir computing utilising photoresponsive properties of ITO/Nb:SrTiO₃ junctions