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Brain-like classifier of temporal patterns
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.ORCID-id: 0000-0002-6032-6155
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap.ORCID-id: 0000-0003-0069-640X
2014 (engelsk)Inngår i: International Conference on Computer and Information Sciences, ICCOINS 2014, Kuala Lumpur, Malaysia, June 03-05, 2014. Proceedings, Piscataway, NJ: IEEE Communications Society, 2014, s. 1-6Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

In this article we present a pattern classification system which uses Vector Symbolic Architecture (VSA) for representation, learning and subsequent classification of patterns, as a showcase we have used classification of vibration sensors measurements to vehicles types. On the quantitative side the proposed classifier requires only 1 kB of memory to classify an incoming signal against of several hundred of training samples. The classification operation into N types requires only 2*N+1 arithmetic operations this makes the proposed classifier feasible for implementation on a low-end sensor nodes. The main contribution of this article is the proposed methodology for representing temporal patterns with distributed representation and VSA-based classifier.

sted, utgiver, år, opplag, sider
Piscataway, NJ: IEEE Communications Society, 2014. s. 1-6
HSV kategori
Forskningsprogram
Kommunikations- och beräkningssystem
Identifikatorer
URN: urn:nbn:se:ltu:diva-26921DOI: 10.1109/ICCOINS.2014.6868349Scopus ID: 2-s2.0-84938789645Lokal ID: 030a0b45-acc7-4a52-a4f6-90ab17f67d98ISBN: 978-1-4799-4391-3 (tryckt)OAI: oai:DiVA.org:ltu-26921DiVA, id: diva2:1000101
Konferanse
International Conference on Computer and Information Sciences : 03/06/2014 - 05/06/2014
Merknad
Godkänd; 2014; 20140513 (denkle)Tilgjengelig fra: 2016-09-30 Laget: 2016-09-30 Sist oppdatert: 2018-07-10bibliografisk kontrollert

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