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dc.contributor.authorSchliebs, S
dc.contributor.authorKasabov, N
dc.date.accessioned2014-03-21T00:49:17Z
dc.date.available2014-03-21T00:49:17Z
dc.date.copyright2013
dc.date.issued2014-03-21
dc.identifier.citationEvolving Systems, vol.4(2), pp.87 - 98
dc.identifier.issn1868-6478
dc.identifier.issn1868-6486
dc.identifier.urihttp://hdl.handle.net/10292/7003
dc.description.abstractThis paper provides a comprehensive literature survey on the evolving Spiking Neural Network (eSNN) architecture since its introduction in 2006 as a further extension of the ECoS paradigm introduced by Kasabov in 1998. We summarize the functioning of the method, discuss several of its extensions and present a number of applications in which the eSNN method was employed. We focus especially on some proposed extensions that allow the processing of spatio-temporal data and for feature and parameter optimisation of eSNN models to achieve better accuracy on classification/prediction problems and to facilitate new knowledge discovery. Finally, some open problems are discussed and future directions highlighted.
dc.publisherSpringer
dc.relation.urihttp://dx.doi.org/10.1007/s12530-013-9074-9
dc.rightsAn author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at www.springerlink.com”. (Please also see Publisher’s Version and Citation).
dc.subjectEvolving spiking neural network
dc.subjectEvolving connectionist systems
dc.subjectSpatio-temporal pattern recognition
dc.titleEvolving spiking neural network - a survey
dc.typeJournal Article
dc.rights.accessrightsOpenAccess
dc.identifier.doi10.1007/s12530-013-9074-9
aut.relation.endpage98
aut.relation.issue2
aut.relation.startpage87
aut.relation.volume4
pubs.elements-id148225


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