id:"swepub:oai:DiVA.org:ltu-26862"
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- Kleyko, DenisLuleå tekniska universitet,Datavetenskap (author)
Modification of Holographic Graph Neuron using Sparse Distributed Representations
- Article/chapterEnglish2016
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- Elsevier,2016
- printrdacarrier
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- LIBRIS-ID:oai:DiVA.org:ltu-26862
- https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-26862URI
- https://doi.org/10.1016/j.procs.2016.07.404DOI
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- Language:English
- Summary in:English
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- Konferensartikel i tidskrift
- This article presents a modification of the recently proposed Holographic Graph Neuron approach for memorizing patterns of generic sensor stimuli. The original approach represents patterns as dense binary vectors, where zeros and ones are equiprobable. The presented modification employs sparse binary distributed representations where the number of ones is less than zeros. Sparse representations are more biologically plausible because activities of real neuronsare sparse. Performance was studied comparing approaches for different sizes of dimensionality.
Subject headings and genre
- NATURVETENSKAP Data- och informationsvetenskap Datavetenskap hsv//swe
- NATURAL SCIENCES Computer and Information Sciences Computer Sciences hsv//eng
- Dependable Communication and Computation Systems
- Kommunikations- och beräkningssystem
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- Osipov, EvgenyLuleå tekniska universitet,Datavetenskap(Swepub:ltu)eao (author)
- Rachkovskij, Dmitri A.International Research and Training Center for Information Technologies and Systems (author)
- Luleå tekniska universitetDatavetenskap (creator_code:org_t)
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- In:Procedia Computer Science: Elsevier88, s. 39-451877-0509
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