How noise affects memory in linear recurrent networks
The effects of noise on memory in a linear recurrent network are theoretically investigated. Memory is characterized by its ability to store previous inputs in its instantaneous state of network, which receives a correlated or uncorrelated noise. Two major properties are revealed: First, the memory...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2025-04-01
|
| Series: | Physical Review Research |
| Online Access: | http://doi.org/10.1103/PhysRevResearch.7.023049 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850184786491998208 |
|---|---|
| author | JingChuan Guan Tomoyuki Kubota Yasuo Kuniyoshi Kohei Nakajima |
| author_facet | JingChuan Guan Tomoyuki Kubota Yasuo Kuniyoshi Kohei Nakajima |
| author_sort | JingChuan Guan |
| collection | DOAJ |
| description | The effects of noise on memory in a linear recurrent network are theoretically investigated. Memory is characterized by its ability to store previous inputs in its instantaneous state of network, which receives a correlated or uncorrelated noise. Two major properties are revealed: First, the memory reduced by noise is uniquely determined by the noise's power spectral density (PSD). Second, the memory will not decrease regardless of noise intensity if the PSD is in a certain class of distribution (including power law). The results are verified using the human brain signals, showing good agreement. |
| format | Article |
| id | doaj-art-e6a07aa0bc9841d9965bc29c9502a52b |
| institution | OA Journals |
| issn | 2643-1564 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | American Physical Society |
| record_format | Article |
| series | Physical Review Research |
| spelling | doaj-art-e6a07aa0bc9841d9965bc29c9502a52b2025-08-20T02:16:56ZengAmerican Physical SocietyPhysical Review Research2643-15642025-04-017202304910.1103/PhysRevResearch.7.023049How noise affects memory in linear recurrent networksJingChuan GuanTomoyuki KubotaYasuo KuniyoshiKohei NakajimaThe effects of noise on memory in a linear recurrent network are theoretically investigated. Memory is characterized by its ability to store previous inputs in its instantaneous state of network, which receives a correlated or uncorrelated noise. Two major properties are revealed: First, the memory reduced by noise is uniquely determined by the noise's power spectral density (PSD). Second, the memory will not decrease regardless of noise intensity if the PSD is in a certain class of distribution (including power law). The results are verified using the human brain signals, showing good agreement.http://doi.org/10.1103/PhysRevResearch.7.023049 |
| spellingShingle | JingChuan Guan Tomoyuki Kubota Yasuo Kuniyoshi Kohei Nakajima How noise affects memory in linear recurrent networks Physical Review Research |
| title | How noise affects memory in linear recurrent networks |
| title_full | How noise affects memory in linear recurrent networks |
| title_fullStr | How noise affects memory in linear recurrent networks |
| title_full_unstemmed | How noise affects memory in linear recurrent networks |
| title_short | How noise affects memory in linear recurrent networks |
| title_sort | how noise affects memory in linear recurrent networks |
| url | http://doi.org/10.1103/PhysRevResearch.7.023049 |
| work_keys_str_mv | AT jingchuanguan hownoiseaffectsmemoryinlinearrecurrentnetworks AT tomoyukikubota hownoiseaffectsmemoryinlinearrecurrentnetworks AT yasuokuniyoshi hownoiseaffectsmemoryinlinearrecurrentnetworks AT koheinakajima hownoiseaffectsmemoryinlinearrecurrentnetworks |