Neuro-Inspired Information Processing

With the end of Moore's law and the emergence of new application needs such as those of the Internet of Things (IoT) or artificial intelligence (AI), neuro-inspired, or neuromorphic, information processing is attracting more and more attention from the scientific community. Its principle is to...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Cappy, Alain
Format: Buch
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 1
container_start_page
container_title
container_volume
creator Cappy, Alain
description With the end of Moore's law and the emergence of new application needs such as those of the Internet of Things (IoT) or artificial intelligence (AI), neuro-inspired, or neuromorphic, information processing is attracting more and more attention from the scientific community. Its principle is to emulate in a simplified way the formidable machine to process information which is the brain, with neurons and artificial synapses organized in network. These networks can be software – and therefore implemented in the form of a computer program – but also hardware and produced by nanoelectronic circuits. The 'material' path allows very low energy consumption, and the possibility of faithfully reproducing the shape and dynamics of the action potentials of living neurons (biomimetic approach) or even being up to a thousand times faster (high frequency approach). This path is promising and welcomed by the major manufacturers of nanoelectronics, as circuits can now today integrate several million neurons and artificial synapses.
doi_str_mv 10.1002/9781119721802
format Book
fullrecord <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_hal_03463840v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>EBC6154245</sourcerecordid><originalsourceid>FETCH-LOGICAL-a33979-3ceb8523761cc2bad84942cd0bed2b08a6dc02467166e0ac1094ba6dcffe4ff23</originalsourceid><addsrcrecordid>eNpVkEFLAzEUhCOiqLVH7z0o4qH6XpJNssdaqi0U9SBeQzabtUu3m5psK_57t65QenrM8DHDG0KuEO4RgD6kUiFiKikqoEekv9cyFcedlkow4JKqU3KBmAAmiWDqjPRjLDPggExigufk5sVtgh_O6rgug8sHs7rwYWWa0teDt-Cta_n685KcFKaKrv9_e-TjafI-ng7nr8-z8Wg-NIylMh0y6zKVUCYFWkszkyuecmpzyFxOM1BG5BYoFxKFcGAsQsqznVkUjhcFZT1y1wUvTKXXoVyZ8KO9KfV0NNc7Dxhv_-CwxT1r4tJ9x4Wvmqi3lcu8X0Z9MErLXndsNIUJpe6YLdUHW7XYbYetg__auNjovzTr6ia05ZPHscCEU56wX6RLbgk</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>book</recordtype><pqid>EBC6154245</pqid></control><display><type>book</type><title>Neuro-Inspired Information Processing</title><source>O'Reilly Online Learning: Academic/Public Library Edition</source><creator>Cappy, Alain</creator><creatorcontrib>Cappy, Alain</creatorcontrib><description>With the end of Moore's law and the emergence of new application needs such as those of the Internet of Things (IoT) or artificial intelligence (AI), neuro-inspired, or neuromorphic, information processing is attracting more and more attention from the scientific community. Its principle is to emulate in a simplified way the formidable machine to process information which is the brain, with neurons and artificial synapses organized in network. These networks can be software – and therefore implemented in the form of a computer program – but also hardware and produced by nanoelectronic circuits. The 'material' path allows very low energy consumption, and the possibility of faithfully reproducing the shape and dynamics of the action potentials of living neurons (biomimetic approach) or even being up to a thousand times faster (high frequency approach). This path is promising and welcomed by the major manufacturers of nanoelectronics, as circuits can now today integrate several million neurons and artificial synapses.</description><edition>1</edition><identifier>ISBN: 9781786304728</identifier><identifier>ISBN: 1786304724</identifier><identifier>EISBN: 9781119721796</identifier><identifier>EISBN: 1119721792</identifier><identifier>EISBN: 9781786304728</identifier><identifier>EISBN: 1786304724</identifier><identifier>EISBN: 9781119721819</identifier><identifier>EISBN: 1119721814</identifier><identifier>DOI: 10.1002/9781119721802</identifier><identifier>OCLC: 1150155638</identifier><language>eng</language><publisher>Newark: John Wiley &amp; Sons, Incorporated</publisher><subject>Engineering Sciences ; Neural networks (Computer science)</subject><creationdate>2020</creationdate><tpages>245</tpages><format>245</format><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-1811-1054</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,306,307,780,784,786,787,885,24761,27924</link.rule.ids><backlink>$$Uhttps://hal.science/hal-03463840$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Cappy, Alain</creatorcontrib><title>Neuro-Inspired Information Processing</title><description>With the end of Moore's law and the emergence of new application needs such as those of the Internet of Things (IoT) or artificial intelligence (AI), neuro-inspired, or neuromorphic, information processing is attracting more and more attention from the scientific community. Its principle is to emulate in a simplified way the formidable machine to process information which is the brain, with neurons and artificial synapses organized in network. These networks can be software – and therefore implemented in the form of a computer program – but also hardware and produced by nanoelectronic circuits. The 'material' path allows very low energy consumption, and the possibility of faithfully reproducing the shape and dynamics of the action potentials of living neurons (biomimetic approach) or even being up to a thousand times faster (high frequency approach). This path is promising and welcomed by the major manufacturers of nanoelectronics, as circuits can now today integrate several million neurons and artificial synapses.</description><subject>Engineering Sciences</subject><subject>Neural networks (Computer science)</subject><isbn>9781786304728</isbn><isbn>1786304724</isbn><isbn>9781119721796</isbn><isbn>1119721792</isbn><isbn>9781786304728</isbn><isbn>1786304724</isbn><isbn>9781119721819</isbn><isbn>1119721814</isbn><fulltext>true</fulltext><rsrctype>book</rsrctype><creationdate>2020</creationdate><recordtype>book</recordtype><sourceid>OODEK</sourceid><recordid>eNpVkEFLAzEUhCOiqLVH7z0o4qH6XpJNssdaqi0U9SBeQzabtUu3m5psK_57t65QenrM8DHDG0KuEO4RgD6kUiFiKikqoEekv9cyFcedlkow4JKqU3KBmAAmiWDqjPRjLDPggExigufk5sVtgh_O6rgug8sHs7rwYWWa0teDt-Cta_n685KcFKaKrv9_e-TjafI-ng7nr8-z8Wg-NIylMh0y6zKVUCYFWkszkyuecmpzyFxOM1BG5BYoFxKFcGAsQsqznVkUjhcFZT1y1wUvTKXXoVyZ8KO9KfV0NNc7Dxhv_-CwxT1r4tJ9x4Wvmqi3lcu8X0Z9MErLXndsNIUJpe6YLdUHW7XYbYetg__auNjovzTr6ia05ZPHscCEU56wX6RLbgk</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Cappy, Alain</creator><general>John Wiley &amp; Sons, Incorporated</general><general>Wiley-ISTE</general><general>Wiley-Blackwell</general><general>Wiley</general><general>ISTE Ltd</general><scope>OHILO</scope><scope>OODEK</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0002-1811-1054</orcidid></search><sort><creationdate>2020</creationdate><title>Neuro-Inspired Information Processing</title><author>Cappy, Alain</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a33979-3ceb8523761cc2bad84942cd0bed2b08a6dc02467166e0ac1094ba6dcffe4ff23</frbrgroupid><rsrctype>books</rsrctype><prefilter>books</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Engineering Sciences</topic><topic>Neural networks (Computer science)</topic><toplevel>online_resources</toplevel><creatorcontrib>Cappy, Alain</creatorcontrib><collection>O'Reilly Online Learning: Corporate Edition</collection><collection>O'Reilly Online Learning: Academic/Public Library Edition</collection><collection>Hyper Article en Ligne (HAL)</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cappy, Alain</au><format>book</format><genre>book</genre><ristype>BOOK</ristype><btitle>Neuro-Inspired Information Processing</btitle><date>2020</date><risdate>2020</risdate><issue>1</issue><isbn>9781786304728</isbn><isbn>1786304724</isbn><eisbn>9781119721796</eisbn><eisbn>1119721792</eisbn><eisbn>9781786304728</eisbn><eisbn>1786304724</eisbn><eisbn>9781119721819</eisbn><eisbn>1119721814</eisbn><abstract>With the end of Moore's law and the emergence of new application needs such as those of the Internet of Things (IoT) or artificial intelligence (AI), neuro-inspired, or neuromorphic, information processing is attracting more and more attention from the scientific community. Its principle is to emulate in a simplified way the formidable machine to process information which is the brain, with neurons and artificial synapses organized in network. These networks can be software – and therefore implemented in the form of a computer program – but also hardware and produced by nanoelectronic circuits. The 'material' path allows very low energy consumption, and the possibility of faithfully reproducing the shape and dynamics of the action potentials of living neurons (biomimetic approach) or even being up to a thousand times faster (high frequency approach). This path is promising and welcomed by the major manufacturers of nanoelectronics, as circuits can now today integrate several million neurons and artificial synapses.</abstract><cop>Newark</cop><pub>John Wiley &amp; Sons, Incorporated</pub><doi>10.1002/9781119721802</doi><oclcid>1150155638</oclcid><tpages>245</tpages><edition>1</edition><orcidid>https://orcid.org/0000-0002-1811-1054</orcidid></addata></record>
fulltext fulltext
identifier ISBN: 9781786304728
ispartof
issn
language eng
recordid cdi_hal_primary_oai_HAL_hal_03463840v1
source O'Reilly Online Learning: Academic/Public Library Edition
subjects Engineering Sciences
Neural networks (Computer science)
title Neuro-Inspired Information Processing
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-08T15%3A25%3A06IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=book&rft.btitle=Neuro-Inspired%20Information%20Processing&rft.au=Cappy,%20Alain&rft.date=2020&rft.issue=1&rft.isbn=9781786304728&rft.isbn_list=1786304724&rft_id=info:doi/10.1002/9781119721802&rft_dat=%3Cproquest_hal_p%3EEBC6154245%3C/proquest_hal_p%3E%3Curl%3E%3C/url%3E&rft.eisbn=9781119721796&rft.eisbn_list=1119721792&rft.eisbn_list=9781786304728&rft.eisbn_list=1786304724&rft.eisbn_list=9781119721819&rft.eisbn_list=1119721814&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=EBC6154245&rft_id=info:pmid/&rfr_iscdi=true