guest ::
| Home > Publications database > Bio-inspired sequence learning mechanisms and their implementation in a memristive neuromorphic hardware > print |
| Home > Publications database > Bio-inspired sequence learning mechanisms and their implementation in a memristive neuromorphic hardware > print |
| 001 | 1022226 | ||
| 005 | 20250203103345.0 | ||
| 024 | 7 | _ | |a 10.34734/FZJ-2024-01347 |2 datacite_doi |
| 037 | _ | _ | |a FZJ-2024-01347 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Bouhadjar, Younes |0 P:(DE-Juel1)176778 |b 0 |e Corresponding author |
| 111 | 2 | _ | |a Neuromorphic, Natural and Physical Computing |g NNPC |c Hannover |d 2023-10-25 - 2023-10-27 |w Germany |
| 245 | _ | _ | |a Bio-inspired sequence learning mechanisms and their implementation in a memristive neuromorphic hardware |
| 260 | _ | _ | |c 2023 |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a Other |2 DataCite |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a LECTURE_SPEECH |2 ORCID |
| 336 | 7 | _ | |a Conference Presentation |b conf |m conf |0 PUB:(DE-HGF)6 |s 1710403695_31139 |2 PUB:(DE-HGF) |x After Call |
| 520 | _ | _ | |a We present a sequence learning model that explains how biological networks learn to predict upcoming elements, signal non-anticipated events, and recall sequences in response to a cue signal. The model accounts for anatomical and electrophysiological properties of cortical neuronal circuits and learns complex sequences in an unsupervised manner using known biological plasticity and homeostatic control mechanisms. We further investigate the feasibility of implementing the sequence learning model on dedicated hardware mimicking brain properties, specifically focusing on memristive crossbar arrays. Finally, we apply the model to sequence classification and anomaly detection in streams of real-world data, and discuss the role of dendritic branches for the sequence learning capacity. |
| 536 | _ | _ | |a 574 - Theory, modelling and simulation (POF3-574) |0 G:(DE-HGF)POF3-574 |c POF3-574 |f POF III |x 0 |
| 536 | _ | _ | |a 5232 - Computational Principles (POF4-523) |0 G:(DE-HGF)POF4-5232 |c POF4-523 |f POF IV |x 1 |
| 536 | _ | _ | |a 5234 - Emerging NC Architectures (POF4-523) |0 G:(DE-HGF)POF4-5234 |c POF4-523 |f POF IV |x 2 |
| 536 | _ | _ | |a Advanced Computing Architectures (aca_20190115) |0 G:(DE-Juel1)aca_20190115 |c aca_20190115 |f Advanced Computing Architectures |x 3 |
| 536 | _ | _ | |a HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) |0 G:(EU-Grant)785907 |c 785907 |f H2020-SGA-FETFLAG-HBP-2017 |x 4 |
| 536 | _ | _ | |a HBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539) |0 G:(EU-Grant)945539 |c 945539 |f H2020-SGA-FETFLAG-HBP-2019 |x 5 |
| 536 | _ | _ | |a DFG project 491111487 - Open-Access-Publikationskosten / 2022 - 2024 / Forschungszentrum Jülich (OAPKFZJ) (491111487) |0 G:(GEPRIS)491111487 |c 491111487 |x 6 |
| 700 | 1 | _ | |a Siegel, Sebastian |0 P:(DE-Juel1)174486 |b 1 |u fzj |
| 700 | 1 | _ | |a Diesmann, Markus |0 P:(DE-Juel1)144174 |b 2 |
| 700 | 1 | _ | |a Waser, R. |0 P:(DE-Juel1)131022 |b 3 |u fzj |
| 700 | 1 | _ | |a Neftci, Emre |0 P:(DE-Juel1)188273 |b 4 |u fzj |
| 700 | 1 | _ | |a Wouters, Dirk J. |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Tetzlaff, Tom |0 P:(DE-Juel1)145211 |b 6 |
| 773 | _ | _ | |0 PERI:(DE-600)2193340-6 |x 1553-734X |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/1022226/files/NNPC.pdf |
| 856 | 4 | _ | |y OpenAccess |x icon |u https://juser.fz-juelich.de/record/1022226/files/NNPC.gif?subformat=icon |
| 856 | 4 | _ | |y OpenAccess |x icon-1440 |u https://juser.fz-juelich.de/record/1022226/files/NNPC.jpg?subformat=icon-1440 |
| 856 | 4 | _ | |y OpenAccess |x icon-180 |u https://juser.fz-juelich.de/record/1022226/files/NNPC.jpg?subformat=icon-180 |
| 856 | 4 | _ | |y OpenAccess |x icon-640 |u https://juser.fz-juelich.de/record/1022226/files/NNPC.jpg?subformat=icon-640 |
| 909 | C | O | |o oai:juser.fz-juelich.de:1022226 |p openaire |p open_access |p VDB |p driver |p ec_fundedresources |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)176778 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)174486 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)144174 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)131022 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)188273 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 6 |6 P:(DE-Juel1)145211 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Decoding the Human Brain |1 G:(DE-HGF)POF3-570 |0 G:(DE-HGF)POF3-574 |3 G:(DE-HGF)POF3 |2 G:(DE-HGF)POF3-500 |4 G:(DE-HGF)POF |v Theory, modelling and simulation |x 0 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-523 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Neuromorphic Computing and Network Dynamics |9 G:(DE-HGF)POF4-5232 |x 1 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-523 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Neuromorphic Computing and Network Dynamics |9 G:(DE-HGF)POF4-5234 |x 2 |
| 914 | 1 | _ | |y 2024 |
| 915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
| 915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b PLOS COMPUT BIOL : 2022 |d 2023-10-25 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2023-10-25 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2023-10-25 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0320 |2 StatID |b PubMed Central |d 2023-10-25 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0501 |2 StatID |b DOAJ Seal |d 2023-01-04T15:22:00Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0500 |2 StatID |b DOAJ |d 2023-01-04T15:22:00Z |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b DOAJ : Peer review |d 2023-01-04T15:22:00Z |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0600 |2 StatID |b Ebsco Academic Search |d 2023-10-25 |
| 915 | _ | _ | |a Peer Review |0 StatID:(DE-HGF)0030 |2 StatID |b ASC |d 2023-10-25 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2023-10-25 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1050 |2 StatID |b BIOSIS Previews |d 2023-10-25 |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2023-10-25 |
| 915 | _ | _ | |a IF < 5 |0 StatID:(DE-HGF)9900 |2 StatID |d 2023-10-25 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-6-20090406 |k INM-6 |l Computational and Systems Neuroscience |x 0 |
| 920 | 1 | _ | |0 I:(DE-Juel1)IAS-6-20130828 |k IAS-6 |l Computational and Systems Neuroscience |x 1 |
| 920 | 1 | _ | |0 I:(DE-Juel1)INM-10-20170113 |k INM-10 |l Jara-Institut Brain structure-function relationships |x 2 |
| 920 | 1 | _ | |0 I:(DE-Juel1)PGI-7-20110106 |k PGI-7 |l Elektronische Materialien |x 3 |
| 920 | 1 | _ | |0 I:(DE-Juel1)PGI-10-20170113 |k PGI-10 |l JARA Institut Green IT |x 4 |
| 920 | 1 | _ | |0 I:(DE-Juel1)PGI-15-20210701 |k PGI-15 |l Neuromorphic Software Eco System |x 5 |
| 980 | _ | _ | |a conf |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a UNRESTRICTED |
| 980 | _ | _ | |a I:(DE-Juel1)INM-6-20090406 |
| 980 | _ | _ | |a I:(DE-Juel1)IAS-6-20130828 |
| 980 | _ | _ | |a I:(DE-Juel1)INM-10-20170113 |
| 980 | _ | _ | |a I:(DE-Juel1)PGI-7-20110106 |
| 980 | _ | _ | |a I:(DE-Juel1)PGI-10-20170113 |
| 980 | _ | _ | |a I:(DE-Juel1)PGI-15-20210701 |
| 980 | 1 | _ | |a FullTexts |
| 981 | _ | _ | |a I:(DE-Juel1)IAS-6-20130828 |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|