Hyperseed: Unsupervised Learning With Vector Symbolic Architectures 2024 (English)In: IEEE Transactions on Neural Networks and Learning Systems, ISSN 2162-237X, E-ISSN 2162-2388, Vol. 35, no 5, p. 6583-6597Article in journal (Refereed) Published

Place, publisher, year, edition, pages

IEEE , 2024. Vol. 35, no 5, p. 6583-6597

Keywords [en]

Hyperseed, neuromorphic hardware, self-organizing maps (SOMs), vector symbolic architectures (VSAs)

National Category

Computer Sciences

Research subject

Dependable Communication and Computation Systems

Identifiers

URN: urn:nbn:se:ltu:diva-94924DOI: 10.1109/TNNLS.2022.3211274ISI: 000890842400001PubMedID: 36383581Scopus ID: 2-s2.0-85142777444OAI: oai:DiVA.org:ltu-94924DiVA, id: diva2:1720742

Funder

The Swedish Foundation for International Cooperation in Research and Higher Education (STINT), MG2020-8842

Note

Validerad;2024;Nivå 2;2024-05-21 (joosat);

Funder: Intel Neuro-morphic Research Community Grant to the Luleå University of Technology; Russian Science Foundation during the period of 2020–2021 (Grant 20-71-10116); Centre for Data Analytics and Cognition (CDAC); European Union’s Horizon 2020 Research and Innovation Program, Marie Skłodowska-Curie (Grant 839179);

Available from: 2022-12-20 Created: 2022-12-20 Last updated: 2025-10-21Bibliographically approved

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Osipov, Evgeny

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