Generalization of Neural Networks on Second-Order Hypercomplex Numbers

Generalization of Neural Networks on Second-Order Hypercomplex Numbers

The vast majority of existing neural networks operate by rules set within the algebra of real numbers. However, as theoretical understanding of the fundamentals of neural networks and their practical applications grow stronger, new problems arise, which require going beyond such algebra. Various tas...

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Bibliographic Details
Main Authors: Stanislav Pavlov, Dmitry Kozlov, Mikhail Bakulin, Aleksandr Zuev, Andrey Latyshev, Alexander Beliaev
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Mathematics
Subjects:
deep learning
hypercomplex neural networks
complex numbers
dual numbers
double numbers
hypercomplex norm
Online Access:https://www.mdpi.com/2227-7390/11/18/3973

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https://www.mdpi.com/2227-7390/11/18/3973

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