Journal article 495 views 195 downloads
A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems
Yuzheng Guo 
,
Xiaolong Zou,
Yifan Hu,
Yifei Yang,
Xinxin Wang,
Yuhan He,
Ruikai Kong,
Yuzheng Guo,
Guoqi Li,
Wei Zhang,
Si Wu,
Huanglong Li
,
Xiaolong Zou,
Yifan Hu,
Yifei Yang,
Xinxin Wang,
Yuhan He,
Ruikai Kong,
Yuzheng Guo,
Guoqi Li,
Wei Zhang,
Si Wu,
Huanglong Li
Advanced Intelligent Systems, Volume: 3, Issue: 11, Pages: 2100054 - 2100054
Swansea University Author:
Yuzheng Guo
-
PDF | Version of Record
© 2021 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Download (4.86MB)
DOI (Published version): 10.1002/aisy.202100054
Abstract
Neuromorphic electronics, an emerging field that aims for building electronic mimics of the biological brain, holds promise for reshaping the frontiers of information technology and enabling a more intelligent and efficient computing paradigm. As their biological brain counterpart, the neuromorphic...
| Published in: | Advanced Intelligent Systems |
|---|---|
| ISSN: | 2640-4567 2640-4567 |
| Published: |
Wiley
2021
|
| Online Access: |
Check full text
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa58919 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| first_indexed |
2021-12-06T13:44:56Z |
|---|---|
| last_indexed |
2022-01-01T04:25:20Z |
| id |
cronfa58919 |
| recordtype |
SURis |
| fullrecord |
<?xml version="1.0"?><rfc1807><datestamp>2021-12-31T10:33:39.3322705</datestamp><bib-version>v2</bib-version><id>58919</id><entry>2021-12-06</entry><title>A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems</title><swanseaauthors><author><sid>2c285ab01f88f7ecb25a3aacabee52ea</sid><ORCID>0000-0003-2656-0340</ORCID><firstname>Yuzheng</firstname><surname>Guo</surname><name>Yuzheng Guo</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2021-12-06</date><deptcode>GENG</deptcode><abstract>Neuromorphic electronics, an emerging field that aims for building electronic mimics of the biological brain, holds promise for reshaping the frontiers of information technology and enabling a more intelligent and efficient computing paradigm. As their biological brain counterpart, the neuromorphic electronic systems are complex, having multiple levels of organization. Inspired by David Marr's famous three-level analytical framework developed for neuroscience, the advances in neuromorphic electronic systems are selectively surveyed and given significance to these research endeavors as appropriate from the computational level, algorithmic level, or implementation level. Under this framework, the problem of how to build a neuromorphic electronic system is defined in a tractable way. In conclusion, the development of neuromorphic electronic systems confronts a similar challenge to the one neuroscience confronts, that is, the limited constructability of the low-level knowledge (implementations and algorithms) to achieve high-level brain-like (human-level) computational functions. An opportunity arises from the communication among different levels and their codesign. Neuroscience lab-on-neuromorphic chip platforms offer additional opportunity for mutual benefit between the two disciplines.</abstract><type>Journal Article</type><journal>Advanced Intelligent Systems</journal><volume>3</volume><journalNumber>11</journalNumber><paginationStart>2100054</paginationStart><paginationEnd>2100054</paginationEnd><publisher>Wiley</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2640-4567</issnPrint><issnElectronic>2640-4567</issnElectronic><keywords>algorithm levels; codesigns; computational levels; David Marr; implementation levels; neuromorphics; three-level analytical frameworks</keywords><publishedDay>22</publishedDay><publishedMonth>11</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-11-22</publishedDate><doi>10.1002/aisy.202100054</doi><url/><notes/><college>COLLEGE NANME</college><department>General Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>GENG</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>National Natural Science Foundation of China. Grant Numbers: 61974082, 61704096, 61836004;
Youth Elite Scientist Sponsorship (YESS) Program of China Association for Science and Technology (CAST). Grant Number: 2019QNRC001;
Supercomputing Wales. Grant Number: scw1070;
National Key R&D Program of China. Grant Number: 2018YFE0200200;
Tsinghua-IDG/McGovern Brain-X Program, Beijing Science and Technology Program. Grant Numbers: Z181100001518006, Z191100007519009, 2016SZ0102;
CETC Haikang Group-Brain Inspired Computing Joint Research Center</funders><lastEdited>2021-12-31T10:33:39.3322705</lastEdited><Created>2021-12-06T13:41:58.0034695</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering</level></path><authors><author><firstname>Yuzheng</firstname><surname>Guo</surname><orcid>0000-0003-2656-0340</orcid><order>1</order></author><author><firstname>Xiaolong</firstname><surname>Zou</surname><order>2</order></author><author><firstname>Yifan</firstname><surname>Hu</surname><order>3</order></author><author><firstname>Yifei</firstname><surname>Yang</surname><order>4</order></author><author><firstname>Xinxin</firstname><surname>Wang</surname><order>5</order></author><author><firstname>Yuhan</firstname><surname>He</surname><order>6</order></author><author><firstname>Ruikai</firstname><surname>Kong</surname><order>7</order></author><author><firstname>Yuzheng</firstname><surname>Guo</surname><order>8</order></author><author><firstname>Guoqi</firstname><surname>Li</surname><order>9</order></author><author><firstname>Wei</firstname><surname>Zhang</surname><order>10</order></author><author><firstname>Si</firstname><surname>Wu</surname><order>11</order></author><author><firstname>Huanglong</firstname><surname>Li</surname><order>12</order></author></authors><documents><document><filename>58919__21809__89d1a0c0b436494ca18857669b100cbb.pdf</filename><originalFilename>58919.pdf</originalFilename><uploaded>2021-12-06T13:43:59.9690745</uploaded><type>Output</type><contentLength>5098256</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>© 2021 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807> |
| spelling |
2021-12-31T10:33:39.3322705 v2 58919 2021-12-06 A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems 2c285ab01f88f7ecb25a3aacabee52ea 0000-0003-2656-0340 Yuzheng Guo Yuzheng Guo true false 2021-12-06 GENG Neuromorphic electronics, an emerging field that aims for building electronic mimics of the biological brain, holds promise for reshaping the frontiers of information technology and enabling a more intelligent and efficient computing paradigm. As their biological brain counterpart, the neuromorphic electronic systems are complex, having multiple levels of organization. Inspired by David Marr's famous three-level analytical framework developed for neuroscience, the advances in neuromorphic electronic systems are selectively surveyed and given significance to these research endeavors as appropriate from the computational level, algorithmic level, or implementation level. Under this framework, the problem of how to build a neuromorphic electronic system is defined in a tractable way. In conclusion, the development of neuromorphic electronic systems confronts a similar challenge to the one neuroscience confronts, that is, the limited constructability of the low-level knowledge (implementations and algorithms) to achieve high-level brain-like (human-level) computational functions. An opportunity arises from the communication among different levels and their codesign. Neuroscience lab-on-neuromorphic chip platforms offer additional opportunity for mutual benefit between the two disciplines. Journal Article Advanced Intelligent Systems 3 11 2100054 2100054 Wiley 2640-4567 2640-4567 algorithm levels; codesigns; computational levels; David Marr; implementation levels; neuromorphics; three-level analytical frameworks 22 11 2021 2021-11-22 10.1002/aisy.202100054 COLLEGE NANME General Engineering COLLEGE CODE GENG Swansea University National Natural Science Foundation of China. Grant Numbers: 61974082, 61704096, 61836004; Youth Elite Scientist Sponsorship (YESS) Program of China Association for Science and Technology (CAST). Grant Number: 2019QNRC001; Supercomputing Wales. Grant Number: scw1070; National Key R&D Program of China. Grant Number: 2018YFE0200200; Tsinghua-IDG/McGovern Brain-X Program, Beijing Science and Technology Program. Grant Numbers: Z181100001518006, Z191100007519009, 2016SZ0102; CETC Haikang Group-Brain Inspired Computing Joint Research Center 2021-12-31T10:33:39.3322705 2021-12-06T13:41:58.0034695 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering Yuzheng Guo 0000-0003-2656-0340 1 Xiaolong Zou 2 Yifan Hu 3 Yifei Yang 4 Xinxin Wang 5 Yuhan He 6 Ruikai Kong 7 Yuzheng Guo 8 Guoqi Li 9 Wei Zhang 10 Si Wu 11 Huanglong Li 12 58919__21809__89d1a0c0b436494ca18857669b100cbb.pdf 58919.pdf 2021-12-06T13:43:59.9690745 Output 5098256 application/pdf Version of Record true © 2021 The Authors. Advanced Intelligent Systems published by Wiley-VCH GmbH This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. true eng http://creativecommons.org/licenses/by/4.0/ |
| title |
A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems |
| spellingShingle |
A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems Yuzheng Guo |
| title_short |
A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems |
| title_full |
A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems |
| title_fullStr |
A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems |
| title_full_unstemmed |
A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems |
| title_sort |
A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems |
| author_id_str_mv |
2c285ab01f88f7ecb25a3aacabee52ea |
| author_id_fullname_str_mv |
2c285ab01f88f7ecb25a3aacabee52ea_***_Yuzheng Guo |
| author |
Yuzheng Guo |
| author2 |
Yuzheng Guo Xiaolong Zou Yifan Hu Yifei Yang Xinxin Wang Yuhan He Ruikai Kong Yuzheng Guo Guoqi Li Wei Zhang Si Wu Huanglong Li |
| format |
Journal article |
| container_title |
Advanced Intelligent Systems |
| container_volume |
3 |
| container_issue |
11 |
| container_start_page |
2100054 |
| publishDate |
2021 |
| institution |
Swansea University |
| issn |
2640-4567 2640-4567 |
| doi_str_mv |
10.1002/aisy.202100054 |
| publisher |
Wiley |
| college_str |
Faculty of Science and Engineering |
| hierarchytype |
|
| hierarchy_top_id |
facultyofscienceandengineering |
| hierarchy_top_title |
Faculty of Science and Engineering |
| hierarchy_parent_id |
facultyofscienceandengineering |
| hierarchy_parent_title |
Faculty of Science and Engineering |
| department_str |
School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - General Engineering |
| document_store_str |
1 |
| active_str |
0 |
| description |
Neuromorphic electronics, an emerging field that aims for building electronic mimics of the biological brain, holds promise for reshaping the frontiers of information technology and enabling a more intelligent and efficient computing paradigm. As their biological brain counterpart, the neuromorphic electronic systems are complex, having multiple levels of organization. Inspired by David Marr's famous three-level analytical framework developed for neuroscience, the advances in neuromorphic electronic systems are selectively surveyed and given significance to these research endeavors as appropriate from the computational level, algorithmic level, or implementation level. Under this framework, the problem of how to build a neuromorphic electronic system is defined in a tractable way. In conclusion, the development of neuromorphic electronic systems confronts a similar challenge to the one neuroscience confronts, that is, the limited constructability of the low-level knowledge (implementations and algorithms) to achieve high-level brain-like (human-level) computational functions. An opportunity arises from the communication among different levels and their codesign. Neuroscience lab-on-neuromorphic chip platforms offer additional opportunity for mutual benefit between the two disciplines. |
| published_date |
2021-11-22T04:15:49Z |
| _version_ |
1763754062305558528 |
| score |
11.012678 |