| Presentation | 2019-12-06 Implementation of Cerebellar Spiking Neural Network Model on a FPGA Yusuke Shinji, Hirotsugu Okuno, Yutaka Hirata, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The cerebellum is crucially involved in motor control and learning. Its neuronal network architecture and firing properties of the neuron types constituting the cerebellar cortical network have been identified by anatomical and physiological studies for the past four decades. Several artificial cerebellums, namely mathematical models of the cerebellum, have been constructed by referring to such anatomical/physiological evidence to understand neural basis of motor control and learning, envisioning applications to real-world robotics. One of the distinctive characteristics of the cerebellum is a large number of neurons forming the neural network. Thus, simulating a realistic artificial cerebellum requires abundant computational power and resources, and running it in realtime for real-world robotics applications is quite challenging. In this study, we implemented an artificial cerebellum on a field-programmable gate array (FPGA) that is characterized as compact, lightweight, low power consumption, and parallel computing. We applied this FPGA artificial cerebellum to real-world adaptive control of a direct-current motor as a simple example, and demonstrated its effectiveness in comparison with an ordinary feedback controller. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Artificial Cerebellum / Spiking Neural Network / FPGA / Adaptive Control |
| Paper # | MBE2019-46,NC2019-37 |
| Date of Issue | 2019-11-29 (MBE, NC) |
| Conference Information | |
| Committee | NC / MBE |
|---|---|
| Conference Date | 2019/12/6(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Toyohashi Tech |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Hayaru Shouno(UEC) / Taishin Nomura(Osaka Univ.) |
| Vice Chair | Kazuyuki Samejima(Tamagawa Univ) / Takashi Watanabe(Tohoku Univ.) |
| Secretary | Kazuyuki Samejima(NAIST) / Takashi Watanabe(NTT) |
| Assistant | Takashi Shinozaki(NICT) / Ken Takiyama(TUAT) / Yasuyuki Suzuki(Osaka Univ.) / Akihiro Karashima(Tohoku Inst. of Tech.) |
| Paper Information | |
| Registration To | Technical Committee on Neurocomputing / Technical Committee on ME and Bio Cybernetics |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Implementation of Cerebellar Spiking Neural Network Model on a FPGA |
| Sub Title (in English) | |
| Keyword(1) | Artificial Cerebellum |
| Keyword(2) | Spiking Neural Network |
| Keyword(3) | FPGA |
| Keyword(4) | Adaptive Control |
| 1st Author's Name | Yusuke Shinji |
| 1st Author's Affiliation | Chubu University(Chubu Univ.) |
| 2nd Author's Name | Hirotsugu Okuno |
| 2nd Author's Affiliation | Osaka Institute of Technology(OIT) |
| 3rd Author's Name | Yutaka Hirata |
| 3rd Author's Affiliation | Chubu University(Chubu Univ.) |
| Date | 2019-12-06 |
| Paper # | MBE2019-46,NC2019-37 |
| Volume (vol) | vol.119 |
| Number (no) | MBE-327,NC-328 |
| Page | pp.pp.7-12(MBE), pp.7-12(NC), |
| #Pages | 6 |
| Date of Issue | 2019-11-29 (MBE, NC) |