Abstract
Nonlinear dendritic processing appears to be a feature of biological neuronsand would also be of use in many applications of artificial neuralnetworks. This paper presents a model of an initially standard linearnode which uses unsupervised learning to find clusters of inputs withinwhich inactivity at one synapse can occlude the activity at the othersynapses.
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Spratling, M.W., Hayes, G.M. Learning Synaptic Clusters for Nonlinear Dendritic Processing. Neural Processing Letters 11, 17–27 (2000). https://doi.org/10.1023/A:1009634821039
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DOI: https://doi.org/10.1023/A:1009634821039