Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Classifier Optimized for Resource-constrained Pervasive Systems and Energy-efficiency
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0002-8752-2375
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0002-8216-832X
Show others and affiliations
2017 (English)In: International Journal of Computational Intelligence Systems, ISSN 1875-6891, E-ISSN 1875-6883, Vol. 10, no 1, p. 1272-1279Article in journal (Refereed) Published
Abstract [en]

Computational intelligence is often used in smart environment applications in order to determine a user’scontext. Many computational intelligence algorithms are complex and resource-consuming which can beproblematic for implementation devices such as FPGA:s, ASIC:s and low-level microcontrollers. Thesetypes of devices are, however, highly useful in pervasive and mobile computing due to their small size,energy-efficiency and ability to provide fast real-time responses. In this paper, we propose a classi-fier, CORPSE, specifically targeted for implementation in FPGA:s, ASIC:s or low-level microcontrollers.CORPSE has a small memory footprint, is computationally inexpensive, and is suitable for parallel processing.The classifier was evaluated on eight different datasets of various types. Our results show thatCORPSE, despite its simplistic design, has comparable performance to some common machine learningalgorithms. This makes the classifier a viable choice for use in pervasive systems that have limitedresources, requires energy-efficiency, or have the need for fast real-time responses.

Place, publisher, year, edition, pages
Atlantis Press, 2017. Vol. 10, no 1, p. 1272-1279
Keyword [en]
Cellular Automata, FPGA, Energy-efficient
National Category
Computer Sciences Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Mobile and Pervasive Computing; Industrial Electronics
Identifiers
URN: urn:nbn:se:ltu:diva-65869ISI: 000415593600032OAI: oai:DiVA.org:ltu-65869DiVA, id: diva2:1145308
Conference
10th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI), San Bartolome de Tirajana, Spain, Nov 29-Dec 2, 2016
Note

Konferensartikel i tidskrift

Available from: 2017-09-28 Created: 2017-09-28 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

CORPSE.pdf(669 kB)32 downloads
File information
File name FULLTEXT01.pdfFile size 669 kBChecksum SHA-512
1c80f76d70781f45f0f220411059afc571bc20d6be9a6efe2cb6259c012911c355821ceb7581c7d301def912c2d873d0594b711127e9a65b814eccaa056a4342
Type fulltextMimetype application/pdf

Other links

http://www.atlantis-press.com/php/download_paper.php?id=25883367

Authority records BETA

Karvonen, NiklasJimenez, Lara LornaGomez Simon, MiguelNilsson, JoakimHallberg, Josef

Search in DiVA

By author/editor
Karvonen, NiklasJimenez, Lara LornaGomez Simon, MiguelNilsson, JoakimHallberg, Josef
By organisation
Computer ScienceEmbedded Internet Systems Lab
In the same journal
International Journal of Computational Intelligence Systems
Computer SciencesOther Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 32 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 441 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf