Brain-like Integrated Systems Research Group

研究成果

2024

Papers

  1. Y. Sakemi, S. Nobukawa, T. Matsuki, T. Morie, K. Aihara, Learning Reservoir Dynamics with Temporal Self-modulation, Communications Physics, Vol. 7, Article No. 29, Jan. 2024. DOI:10.1038/s42005-023-01500-w

2023

Papers

  1. Y. Sakemi, K. Morino, T. Morie, K. Aihara, A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design, IEEE Trans. Neural Networks and Learning Systems, Vol. 34, Issue 1, pp. 394 - 408, Jan. 2023. (Date of Publication: July 19, 2021). DOI:10.1109/TNNLS.2021.3095068
  2. Y. Sakemi, S. Nobukawa, T. Matsuki, T. Morie, K. Aihara, Learning Reservoir Dynamics with Temporal Self-Modulation, arXiv:2301.09235, Jan. 23, 2023. [without review]

International Conferences (with review)

  1. N. Fuengfusin, H. Tamukoh, Y. Tanaka, O. Nomura, T. Morie, Efficient Repetition Coding for Deep Learning Towards Implementation Using Emerging Non-volatile Memory with Write-errors, Int. Joint Conf. on Neural Networks (IJCNN2023), June, 2023.
  2. K. Yoshioka, Y. Katori, Y. Tanaka, O. Nomura, T. Morie, H. Tamukoh, FPGA Implementation of a Chaotic Boltzmann Machine Annealer, Int. Joint Conf. on Neural Networks (IJCNN2023), June, 2023.

国内発表

  1. 宍戸 優樺, 野村 修, 立野 勝巳, 田向 権, 森江 隆, 海馬機能を模倣したディジタル・アナログ併用脳型メモリ回路コア, LSIとシステムのワークショップ2023, 2023年5月9-10日，優秀ポスター賞（学生部門）

2022

Papers

  1. H. Nakagawa, K. Tateno, K. Takada, T. Morie, A Neural Network Model of the Entorhinal Cortex and Hippocampus for Event-order Memory Processing, IEEE Access, Vol. 10, pp. 43003 - 43012, April 18, 2022. DOI:10.1109/ACCESS.2022.3168715
  2. O. Nomura, Y. Sakemi, T. Hosomi, T. Morie, Robustness of Spiking Neural Networks based on Time-To-First-Spike Encoding against Adversarial Attacks, IEEE Trans. Circuits and Systems II: Express Briefs , Vol. 69, Issue 9, pp. 3640-3644, June 20, 2022. Selected as a best paper in MWSCAS 2022. DOI: 10.1109/TCSII.2022.3184313

International Conferences (with review)

  1. K. Tamai, K. Kawazoe, Y. Shishido, Y. Katori, H. Tamukoh, O. Nomura, T. Morie, Numerical Simulation for Analog VLSI Implementation of Reinforcement Learning Using Reservoir Computing, The 3rd International Symposium on Neuromorphic AI Hardware, P-PM7, March 18-19(19), 2022.
  2. Y. Shishido, K. Kawazoe, K. Tamai, Y. Katori, H. Tamukoh, O. Nomura, T. Morie, A Co-Design Environment for AI Hardware Simulation Using PyLTSpice, The 3rd International Symposium on Neuromorphic AI Hardware, P-PM8, March 18-19(19), 2022. Student Presentation Award
  3. K. Nakahara, Y. Katori, H. Tamukoh, O. Nomura, T. Morie, Memory Capacity of Reservoir Computing Using Chaotic Boltzmann Machines, The 3rd International Symposium on Neuromorphic AI Hardware, P-PM9, March 18-19(19), 2022.
  4. O. Nomura, I. Kawashima, S. Uenohara, Y. Tanaka, A. Mizutani, K. Takada, K. Tateno, H. Tamukoh, T. Morie, A Memory-based LSI Architecture for Entorhinal-hippocampal Model, The 3rd International Symposium on Neuromorphic AI Hardware, P-PM12, March 18-19(19), 2022.
  5. A. Mizutani, Y. Tanaka, I. Kawashima, H. Tamukoh, K. Tateno, T. Morie, Memory-based Action Planning Inspired by Hippocampal Replay, The 3rd International Symposium on Neuromorphic AI Hardware, Oral-4, Online and Kitakyushu, Japan, March 18-19 (18), 2022. Student Presentation Award
  6. I. Kawashima, K. Tateno, T. Morie, H. Tamukoh, A Memory-Based Entorhinal-Hippocampal Model and its FPGA Implementation by On-Chip RAMs, Int. Symp. on Circuits and Systems (ISCAS 2022), (Paper ID 1182, B3L-03.4), Austin, Texas, USA, May 28 - June 1(May 31), 2022.
  7. Y. Sakemi, K. Morino, T. Morie, T. Hosomi, K. Aihara, A Spiking Neural Network with Resistively Coupled Synapses Using Time-to-First-Spike Coding Towards Efficient Charge-Domain Computing, Int. Symp. on Circuits and Systems (ISCAS 2022), pp. 2152-2156 (Paper ID 1324, A1aL-04.3), Online (Virtual Asia), May 28 - June 1(May 30), 2022.
  8. O. Nomura, Y. Sakemi, T. Hosomi, T. Morie, Robustness of Spiking Neural Networks based on Time-To-First-Spike Encoding against Adversarial Attacks, IEEE Int. Midwest Symp. on Circuits and Systems (MWSCAS 2022), Aug. 7-10(10), 2022. Selected as a best paper for publication in IEEE TCAS-II
  9. Y. Shishido, O. Nomura, K. Tateno, H. Tamukoh, T. Morie, CMOS VLSI Implementation of a Hippocampal Conjunctive Place-cue Cells Network, The 4th International Symposium on Neuromorphic AI Hardware, P2-6, Dec. 13-14(14), 2022. Student Presentation Award
  10. K. Tamai, Y. Katori, H. Tamukoh, O. Nomura, T. Morie, Performance Evaluation of a Reservoir Reinforcement Learning Model Considering Nonlinear Write Characteristics of Analog Memory, The 4th International Symposium on Neuromorphic AI Hardware, P2-7, Dec. 13-14(14), 2022. The Best Student Presentation Award
  11. K. Nakahara, Y. Katori, O. Nomura, H. Tamukoh, T. Morie, Evaluation of Modular Reservoirs Using Chaotic Boltzmann Machines, The 4th International Symposium on Neuromorphic AI Hardware, JSPS C2C Session-4/P2-8, Dec. 13-14(14), 2022.
  12. A. Mizutani, I. Kawashima, Y. Tanaka, H. Tamukoh, K. Tateno, O. Nomura, T. Morie, Hardware-oriented Brain-inspired Model with Memory Accumulation and Recall Functions to Generate Actions of Home Service Robots, The 4th International Symposium on Neuromorphic AI Hardware, P2-12, Dec. 13-14(14), 2022. Student Presentation Award

International Conferences (without review)

  1. Y. Shishido, K. Kawazoe, K. Tamai, Y. Katori, H. Tamukoh, O. Nomura, T. Morie, A Co-design Environment for Computational Models and Circuits Using PyLTSpice and Its Application to Circuit Design for Reinforcement Learning Using Reservoir Computing, The 10th RIEC Int. Symp. on Brain Functions and Brain Computer (BFBC2022), GS1-2, Feb. 18-19(19), 2022.
  2. K. Tamai, K. Kawazoe, Y. Shishido, Y. Katori, H. Tamukoh, O. Nomura, T. Morie, Numerical Simulation for VLSI Implementation of Reinforcement Learning Using Reservoir Computing, The 10th RIEC Int. Symp. on Brain Functions and Brain Computer (BFBC2022), GS1-3, Feb. 18-19(19), 2022.
  3. A. Mizutani, Y. Tanaka, H. Tamukoh, Y. Katori, K. Tateno, T. Morie, A Situation-dependent Navigation System by Brain-inspired Neural Networks with Hippocampus, Prefrontal Cortex, and Amygdala Functions, The 10th RIEC Int. Symp. on Brain Functions and Brain Computer (BFBC2022), GS1-4, Feb. 18-19(19), 2022.

Invited Paper/Talk

  1. O. Nomura, Analog Neuromorphic Hardware for Energy-efficient AI Computing, The 18th Embedded Vision Workshop (EVW 2022) In conjunction with CVPR 2022 (New Orleans), Online, June 20, 2022.

国内発表

  1. 野村 修, 森江 隆, 田向 権, 川島 一郎, 中原和勇, 香取 勇一, カオスボルツマンマシンとそのレザバー応用および超低消費電力型LSIの開発​, 電気学会 電子・情報・システム部門大会, TC16:超低消費電力型ニューロモーフィックデバイスとそのアプリケーション, TC16-1, 広島大学（東広島）, 2022年9月2日.
  2. 玉井 克典, 田向 権, 香取 勇一, 野村 修, 森江 隆, アナログメモリの非線形書き込み特性を考慮したリザバー強化学習モデルの性能評価, 第83回応用物理学会 秋季学術講演会, 講演番号21a-C201-7, 東北大学（仙台）, 2022年9月21日.
  3. 水谷 彰伸, 川島 一郎, 田中 悠一朗, 田向 権, 立野 勝巳, 野村 修, 森江 隆, 海馬モデルによる経験の蓄積と想起に基づくホームサービスロボットの行動生成, 電子情報通信学会ニューロコンピューティング研究会, 信学技報, vol. 122, no. 292, NC2022-59, pp. 68-73, 2022年12月.

Major publications related to the projects before 2022

Whole publication list of Brain-like Systems Lab before 2022 is here.

Papers

  1. Y. Sakemi, T. Morie, T. Hosomi, K. Aihara, Effects of VLSI Circuit Constrains on Temporal-Coding Multilayer Spiking Neural Networks, arXiv:2106.10382, June 22, 2021. [without review]
  2. H. Nakagawa, K. Tateno, K. Takada, T. Morie, A Neural Network Model of the Entorhinal Cortex and Hippocampus for Event-order Memory Processing, arXiv:2111.10535, Nov. 20, 2021. [without review]
  3. Y. Sakemi, K. Morino, T. Morie, K. Aihara, A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on Temporal Coding Toward Energy-Efficient VLSI Processor Design, arXiv:2001.05348, Jan. 8, 2020. [without review]
  4. M, Harada, M, Takahashi, S. Sakai, T. Morie, A Time-domain Analog Weighted-sum Calculation Circuit Using Ferroelectric-gate Field-effect Transistors for Artificial Intelligence Processors, Jpn. J. Appl. Phys., Vol. 59, No. 4, pp. 040604-1-12, Apr. 1, 2020. (Free article)
  5. Y. Ishida, T. Morie, H. Tamukoh, A hardware intelligent processing accelerator for domestic service robots, Advanced Robotics, Vol. 34, Issue 14, pp. 947-957, Jun. 2020.
  6. I. Kawashima, T. Morie, H. Tamukoh, FPGA Implementation of Hardware-Oriented Chaotic Boltzmann Machines, IEEE Access, Vol. 8, pp. 204360-204377, Nov. 2020. (DOI:10.1109/ACCESS.2020.3036882 (Free article))
  7. Y. Tanaka, T. Morie, H. Tamukoh, An Amygdala-Inspired Classical Conditioning Model on an FPGA for Home Service Robots, IEEE Access, Vol. 8, pp. 212066-212078, Nov. 2020. (DOI:10.1109/ACCESS.2020.3038161 (Free article))
  8. M. Yamaguchi, G. Iwamoto, Y. Nishimura, H. Tamukoh, T. Morie, An Energy-efficient Time-domain Analog CMOS BinaryConnect Neural Network Processor Based on a Pulse-width Modulation Approach, IEEE Access, Vol. 9, pp. 2644-2654, Dec. 2020. (DOI:10.1109/ACCESS.2020.3047619 (Free article))
  9. M. Yamaguchi, G. Iwamoto, H. Tamukoh, T. Morie, An Energy-efficient Time-domain Analog VLSI Neural Network Processor Based on a Pulse-width Modulation Approach, arXiv:1902.07707, Feb. 16. 2019. [without review]
  10. Q. Wang, H. Tamukoh, T. Morie, A Time-domain Analog Weighted-sum Calculation Model for Extremely Low Power VLSI Implementation of Multi-layer Neural Networks, arXiv:1810.06819, Oct. 2018. [without review]
  11. T. Tohara, H. Liang, H. Tanaka, M. Igarashi, S. Samukawa, K. Endo, Y. Takahashi, T. Morie, Silicon Nanodisk Array with a Fin Field-effect Transistor for Time-domain Weighted Sum Calculation toward Massively Parallel Spiking Neural Networks, Appl. Phys. Express, Vol. 9, No. 3, 034201, Feb. 12, 2016. (DOI: 10.7567/APEX.9.034201 (Open Access))

International Conferences (with review)

  1. A. Mizutani, Y. Tanaka, H. Tamukoh, Y. Katori, K. Tateno, T. Morie, Brain-inspired neural network navigation system with hippocampus, prefrontal cortex, and amygdala functions, 2021 Int. Symp. on Intelligent Signal Processing and Communication Systems (ISPACS 2021), BS-06, Online, Nov. 16-19 (17), 2021. Best Student Paper Award
  2. I. Kawashima, Y. Katori, T. Morie, H. Tamukoh, An area-efficient multiply-accumulation architecture and implementations for time-domain neural processing, Int. Conf. on Field-Programmable Technology (ICFPT 2021), pp. 1-4, Online, Dec. 6-10 (9), 2021.
  3. Y. Tanaka, H. Tamukoh, K. Tateno, Y. Katori, and T. Morie, A Brain-inspired Artificial Intelligence Model of Hippocampus, Amygdala, and Prefrontal Cortex on Home Service Robots, Proc. of the 2020 Int. Symp. on Nonlinear Theory and Its Applications (NOLTA2020), pp. 138-141, Virtual, Nov. 16-19(16), 2020. Student Paper Award
  4. M. Inada, Y. Tanaka, H. Tamukoh, K. Tateno, T. Morie, and Y. Katori, A Reservoir Based Q-learning Model for Autonomous Mobile Robots, Proc. of the 2020 Int. Symp. on Nonlinear Theory and Its Applications (NOLTA2020), pp. 213-216, Virtual, Nov. 16-19(17), 2020.
  5. M. Yamaguchi, G. Iwamoto, Y. Abe, Y. Tanaka, Y. Ishida, H. Tamukoh, T. Morie, Live Demonstration: A VLSI Implementation of Time-Domain Analog Weighted-Sum Calculation Model for Intelligent Processing on Robots, Int. Symp. on Circuits and Systems (ISCAS 2019), Paper 2353, Live Demo, Sapporo, Japan, May 26-29(27), 2019. Best Live Demonstration Award
  6. Y. Katori, H. Tamukoh, T. Morie, Reservoir Computing Based on Dynamics of Pseudo-Billiard System in Hypercube, Int. Joint Conf. on Neural Networks (IJCNN 2019), Paper N-20372(8 pages), Budapest, Hungary, July 14-19(17), 2019. Best Paper Award
  7. M. Yamaguchi, Y. Katori, D. Kamimura, H. Tamukoh, T. Morie, A Chaotic Boltzmann Machine Working as a Reservoir and Its Analog VLSI Implementation, Int. Joint Conf. on Neural Networks (IJCNN 2019), Paper N-20163(7 pages), Budapest, Hungary, July 14-19(17), 2019.
  8. M. Inada, Y. Tanaka, H. Tamukoh, K. Tateno, T. Morie, Y. Katori, Prediction of Sensory Information and Generation of Motor Commands for Autonomous Mobile Robots Using Reservoir Computing, Proc. of the 2019 Int. Symp. on Nonlinear Theory and its Applications (NOLTA2019), pp. 333-336, Kuala Lumpur, Malaysia, Dec. 2-6(4), 2019.
  9. Y. Ishida, T. Morie, H. Tamukoh, Live Demonstration: A Hardware Accelerated Robot Middleware Package for Intelligent Processing on Robots, Int. Symp. on Circuits and Systems (ISCAS 2018), C2P-U (Demo Session), Florence, Italy, May 27-30(30), 2018.
  10. M. Yamaguchi, H. Tamukoh, H. Suzuki, T. Morie, A CMOS Chaotic Boltzmann Machine Circuit and Three-neuron Network Operation, Proc. Int. Joint Conf. on Neural Networks (IJCNN 2017), pp. 1218-1224, Anchorage, Alaska, USA, May 14-19(15), 2017.
  11. Y. Ishida, Y. Tanaka, S. Hori, Y. Kiyama, Y. Kuroda, M. Hisano, H. Fujita, Y. Yoshimoto, Y. Aratani, G. Iwamoto, K. Hashimoto, D. Pramanta, Y. Abe, T. Morie, H. Tamukoh, Approach to accelerate the development of practical home service robots - RoboCup@Home DSPL - (Invited), 26th IEEE Int. Symp. on Robot and Human Interactive Communication (RO-MAN 2017), RO-MAN Workshop: HRI for Service Robots in RoboCup@Home, Lisbon, Portugal, Aug. 28 - Sep. 1 (Sep. 1), 2017.

解説記事・招待論文

  1. 森江 隆,【解説記事】ニューロモルフィックシステムと物理デバイス, 応用物理（応用物理学会機関誌）88巻7号, 基礎講座（No. 35）「応用物理と人工知能」, pp. 481-485,　2019年7月. (DOI:10.11470/oubutsu.88.7_481) [in Japanese]
  2. 石井 信, 岡田 真人, 菅生 康子, 大羽 成征, 山崎 匡, 森江 隆, 國吉 康夫,【解説記事】脳型人工知能技術の開発, 人工知能, Vol. 34, No. 6, pp. 817-825, Nov., 2019. [in Japanese]
  3. 森江 隆,【招待論文】脳型アナログ演算と専用集積回路, 人工知能, Vol. 33, No. 1, pp. 39-44, Jan., 2018. [in Japanese]
  4. T. Morie, Time-domain Analog Computing and VLSI Systems toward Ultimately High-efficient Brain-like Hardware (Invited), Workshop on Brain-inspired Hardware, sponsored by AIST, Tokyo, Japan, March 30, 2017. (Presentation slides)