Polytechnic and design, Vol. 9 No. 2, 2021.
Professional paper
https://doi.org/10.19279/TVZ.PD.2021-9-2-06
KNOWLEDGE AND LEARNING OF A SINGLE NEURON
Predrag Valožić
; Zagreb University of Applied Sciences, Zagreb, Croatia, retired professor
Abstract
The learning outcomes of a linear artificial neuron with different prior knowledge were analyzed. Based on a common mathematical model of neurons and the same template for learning, the properties of different learning models more or less mathematized are illustrated with examples. It has been shown that "more advanced" models are faster but more sensitive and rigid in the solutions offered. "Childish", basic learning models are slower but more universal and "imaginative". A common criterion for assessing the "learning outcome" is the correctness of the solution to the problem – the design of a recursive sine wave generator of certain features: amplitude and frequency.
Keywords
Linear neuron; learning; linear combination; inverse; pseudoinverse; feedback
Hrčak ID:
273767
URI
Publication date:
20.7.2021.
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