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dc.contributor.authorLyon, C.
dc.contributor.authorDavey, N.
dc.date.accessioned2010-07-26T13:39:29Z
dc.date.available2010-07-26T13:39:29Z
dc.date.issued1993
dc.identifier.citationLyon , C & Davey , N 1993 , The use of metrics in connectionist psychological models . UH Computer Science Technical Report , vol. 157 , University of Hertfordshire .
dc.identifier.otherPURE: 98596
dc.identifier.otherPURE UUID: 1a34ea96-08fe-4cc0-b7cf-8a8d03034f8a
dc.identifier.otherdspace: 2299/4689
dc.identifier.urihttp://hdl.handle.net/2299/4689
dc.description.abstractModels of psychological and cognitive phenomena that are based on connectionist processing have recently been described. These include Norris's back propagation model, Schyns's model based on Kohonen nets and Hinton and Shallice's model that adds a recurrent layer to an MLP type network. This paper looks at some of the ways data are represented and at the metrics that are employed in these models. It investigates the techniques that are appropriate for different processing tasks in connectionist networks. The term "connectionist network" is an alternative to "neural network", which is the name more often used in the computer science literature.en
dc.language.isoeng
dc.publisherUniversity of Hertfordshire
dc.relation.ispartofseriesUH Computer Science Technical Report
dc.titleThe use of metrics in connectionist psychological modelsen
dc.contributor.institutionSchool of Computer Science
dc.contributor.institutionScience & Technology Research Institute
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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