Högskolan i Skövde

his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • 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
Artificial neural networks in models of specialisation, guild evolution and sympatric speciation
University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Life Sciences.ORCID iD: 0000-0003-3000-8786
University of Skövde, The Systems Biology Research Centre. University of Skövde, School of Life Sciences.ORCID iD: 0000-0002-2055-4284
2010 (English)In: Modelling Perception in Artificial Neural Networks / [ed] Colin R. Tosh & Graeme D. Ruxton, Cambridge University Press, 2010, p. 236-254Chapter in book (Other academic)
Place, publisher, year, edition, pages
Cambridge University Press, 2010. p. 236-254
National Category
Natural Sciences
Research subject
Natural sciences
Identifiers
URN: urn:nbn:se:his:diva-4324Scopus ID: 2-s2.0-84926115087ISBN: 9780521763950 ISBN: 9780511779145 OAI: oai:DiVA.org:his-4324DiVA, id: diva2:345434
Available from: 2010-08-25 Created: 2010-08-25 Last updated: 2017-11-27Bibliographically approved

Open Access in DiVA

No full text in DiVA

Scopus

Authority records

Holmgren, Noel M. A.Norrström, Niclas

Search in DiVA

By author/editor
Holmgren, Noel M. A.Norrström, Niclas
By organisation
The Systems Biology Research CentreSchool of Life Sciences
Natural Sciences

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 1042 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • apa-cv
  • 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