Supervised and unsupervised learning in processing myographic patterns

• Published in: Journal of physics. Conference series Vol. 1117; no. 1; pp. 12008 - 12016
• Main Authors: Shamsin, M, Krilova, N, Bazhanova, M, Kazantsev, V, Makarov, V A, Lobov, S
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.11.2018
• Subjects: Artificial neural networks; Cerebral cortex; Classification; Clustering; Electromyography; Error correction; Learning theory; Man-machine interfaces; Multilayer perceptrons; Recognition; Self organizing maps; Supervised learning; Unsupervised learning

Synaptic connections in neocortex are assumed to be formed by a self-organizing process leading to emergence of the so-called self-organized maps (SOMs). Formation of SOMs is based on the unsupervised Hebbian learning rule, according to which the weight of a synaptic connection depends on the co-act...