Session Details

[24a-31A-1~9]FS.1 Focused Session "AI Electronics"

Sun. Mar 24, 2024 9:00 AM - 11:30 AM JST
Sun. Mar 24, 2024 12:00 AM - 2:30 AM UTC
31A (Building No. 3)
Kensuke Ota(Sony Semiconductor Solutions), Takao Marukame(Toshiba)

[24a-31A-1]Analog Photonics Simulation Based on Hardware Experiment:
Case Studies for Large-Scale AI-Model and LORA-Based Fine Tuning

〇Mitsumasa Nakajima1, Kohei Ikeda2, Satoshi Kawakami3, Toshikazu Hashimoto1 (1.NTT Device Technology Labs., 2.NTT Basic Research Labs., 3.Kyusyu Univ.)

[24a-31A-2]Additional operations for online learning on optical reservoir computing

〇Toshikazu Hashimoto1, Mitsumasa Nakajima1 (1.NTT Device Technology Labs)

[24a-31A-3]Performance Evaluation of Multi-path Interference-based On-Chip Photonic Reservoir Computing Circuit

〇Keigo Takabayashi1, Tomoya Yamaguchi1, Tomoaki Niiyama1, Satoshi Sunada1 (1.Kanazawa Univ)

[24a-31A-4]Demonstration of the online learning on the magneto-optical diffractive deep neural network

〇(D)Hotaka Sakaguchi1, Riku Oya1, Jian Zhang1, Takuma Honma1, Satoshi Sumi2, Hiroyuki Awano2, Hirofumi Nonaka3, Fatima Zahra Chafi1, Takayuki Ishibashi1 (1.Nagaoka Univ. of Tech., 2.Toyota Tech. Inst., 3.Aichi Inst. of Tech.)

[24a-31A-5]Traveling Distance Estimation in an Amoeba-inspired Autonomous Walking Robot
for Behavior Development

〇Kazuki Matsuda1, Seiya Kasai1 (1.Hokkaido Univ.)

[24a-31A-6]Dimension extension of Pavlovian conditioning with miniaturized four-terminal planar TiO2-x memristors

〇(M2)Ryohei Yamamoto1, Yusuke Hayashi1, Tetsuya Tohei1, Akira Sakai1 (1.Osaka Univ.)

[24a-31A-7]Development and Resistive Switching Properties of Amorphous GaOx Four-Terminal Crossbar Array Memristor

〇(M1)Naoya Yamashita1, Yusuke Hayashi1, Tetsuya Tohei1, Akira Sakai1 (1.Osaka Univ.)

[24a-31A-8]Implementation of Operant Conditioning in Four-Terminal Planar TiO2-x Memristive Devices

〇(M1)Zijie Meng1, Yusuke Hayashi1, Tetsuya Tohei1, Akira Sakai1 (1.School of Engineering Science, Osaka Univ.)

[24a-31A-9]Large improvement in blood glucose prediction accuracy by reducing noise in the echo-state network

〇Yifan Geng1, Takeaki Yajima1 (1.Kyushu Univ.)