Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Physical reservoir computing (PRC) using synaptic devices has attracted attention as a promising edge artificial intelligence device. To handle time-series data on various time scales, it is necessary to fabricate devices with the desired time scale. In this study, we fabricated a dye-sensitized solar-cell-based synaptic device with controllable time constants by changing the light intensity. This device showed synaptic features, such as paired-pulse facilitation and paired-pulse depression, in response to light intensity. Moreover, we found that the high computational performance of the time-series data processing task was achieved by changing the light intensity, even when the input pulse width was varied. In addition, the fabricated device can be used for motion recognition tasks. This study paves the way for realizing multiple time-scale PRC.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1021/acsami.4c11061 | DOI Listing |
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