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AMSOM: artificial metaplasticity in SOM neural networks—application to MIT-BIH arrhythmias database.

Authors :
Torres-Alegre, Santiago
Fombellida, Juan
Piñuela-Izquierdo, Juan Antonio
Andina, Diego
Source :
Neural Computing & Applications. Sep2020, Vol. 32 Issue 17, p13213-13220. 8p.
Publication Year :
2020

Abstract

Artificial metaplasticity is the machine learning algorithm inspired in the biological metaplasticity of neural synapses. Metaplasticity stands for plasticity of plasticity, and as long as plasticity is related to memory, metaplasticity is related to learning. Implemented in supervised learning assuming input patterns distribution or a related function, it has proved to be very efficient in performance and in training convergence for multidisciplinary applications. Now, for the first time, this kind of artificial metaplasticity is implemented in an unsupervised neural network, achieving also excellent results that are presented in this paper. To compare results, a modified self-organization map is applied to the classification of MIT-BIH cardiac arrhythmias database. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09410643
Volume :
32
Issue :
17
Database :
Academic Search Index
Journal :
Neural Computing & Applications
Publication Type :
Academic Journal
Accession number :
145259039
Full Text :
https://doi.org/10.1007/s00521-018-3576-0