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SMETANA, B. CHVALINA, J.
Original Title
Models of Iterated Artificial Neurons
Type
conference paper
Language
English
Original Abstract
Abstract. Application of algebraic structures in research of structure of the most used artificial neural network - multilayer perceptron and functionality of artificial neuron, is one from current the most interesting areas in the usage of time varying artificial neurons. In this paper, we have described certain properties of constructed algebraic structures of artificial neurons, including the hypergroup formed by iterated models of artificial neurons. We describe constructions of P-hypergroups - a certain special case of which are variants of semigroups - of artificial time-varying neurons based on investigations of Vougiouklis - Konguetsof and also construction of the cascade with the phase set of neurons. These concepts yield a base for the building of algebraic systems of artificial neurons which deserves to be developed.
Keywords
P-hypergroups, iterated models, artificial neurons, groups of neurons.
Authors
SMETANA, B.; CHVALINA, J.
Released
5. 2. 2019
Publisher
Slovak University of Technology in Bratislava, Faculty of Mechanical Engineering
Location
Bratislava
ISBN
978-80-227-4884-1
Book
18th CONFERENCE ON APPLIED MATHEMATICS APLIMAT 2019 PROCEEDINGS
Pages from
203
Pages to
2012
Pages count
10
URL
http://evlm.stuba.sk/APLIMAT/indexe.htm
BibTex
@inproceedings{BUT156491, author="Jan {Chvalina} and Bedřich {Smetana}", title="Models of Iterated Artificial Neurons", booktitle="18th CONFERENCE ON APPLIED MATHEMATICS APLIMAT 2019 PROCEEDINGS", year="2019", pages="203--2012", publisher="Slovak University of Technology in Bratislava, Faculty of Mechanical Engineering", address="Bratislava", isbn="978-80-227-4884-1", url="http://evlm.stuba.sk/APLIMAT/indexe.htm" }