Learning synaptic clusters for non-linear dendritic processing

Michael W. Spratling, Gillian M. Hayes

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)
353 Downloads (Pure)

Abstract

Nonlinear dendritic processing appears to be a feature of biological neurons and would also be of use in many applications of artificial neural networks. This paper presents a model of an initially standard linear node which uses unsupervised learning to find clusters of inputs within which inactivity at one synapse can occlude the activity at the other synapses.
Original languageEnglish
Article numberN/A
Pages (from-to)17 - 27
Number of pages11
JournalNEURAL PROCESSING LETTERS
Volume11
Issue number1
DOIs
Publication statusPublished - Feb 2000

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