| Presentation | 2022-03-29 Effects of sparse connections in spiking neural networks for unsupervised pattern recognition Hiroki Shinagawa, Kantaro Fujiwara, Gouhei Tanaka, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Recently, the spiking neural network (SNN) models, which compute using spatio-temporal information representation by neuronal firing phenomena (it calls spikes), have been applied for the machine learning tasks. In this presentation, we focus on the SNN model with spike timing dependent plasticity used for unsupervised pattern recognition, and report the results of investigating the effect of sparsity of synaptic connections on recognition performance and computational time. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Spiking neural networks / SNN / Un-supervised learning / Pattern recognition / Sparse connection |
| Paper # | MSS2021-69,NLP2021-140 |
| 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) | Effects of sparse connections in spiking neural networks for unsupervised pattern recognition |
| Sub Title (in English) | |
| Keyword(1) | Spiking neural networks |
| Keyword(2) | SNN |
| Keyword(3) | Un-supervised learning |
| Keyword(4) | Pattern recognition |
| Keyword(5) | Sparse connection |
| 1st Author's Name | Hiroki Shinagawa |
| 1st Author's Affiliation | The University of Tokyo(Univ. of Tokyo) |
| 2nd Author's Name | Kantaro Fujiwara |
| 2nd Author's Affiliation | The University of Tokyo(Univ. of Tokyo) |
| 3rd Author's Name | Gouhei Tanaka |
| 3rd Author's Affiliation | The University of Tokyo(Univ. of Tokyo) |
| Date | 2022-03-29 |
| Paper # | MSS2021-69,NLP2021-140 |
| Volume (vol) | vol.121 |
| Number (no) | MSS-443,NLP-444 |
| Page | pp.pp.71-76(MSS), pp.71-76(NLP), |
| #Pages | 6 |
| Date of Issue | 2022-03-21 (MSS, NLP) |