Complex, Hypercomplex and Fuzzy-Valued Neural Networks: New Perspectives and Applications (1)

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Synopsis
Complex, Hypercomplex, and Fuzzy-Valued Neural Networks are extensions of classical neural networks to higher dimensions. In recent decades, this theory has emerged as a forefront in neural networks theory. There are several approaches to extend classical neural network models: quaternionic analysis, which merely uses quaternions; Clifford analysis, which relies on Clifford algebras; and finally generalizations of complex variables to higher dimensions. This book reflects a selection of papers related to complex, hypercomplex analysis, and fuzzy approaches applied to neural networks theory. The topics covered represent new perspectives and current trends in neural networks and their applications to mathematical physics, image analysis and processing, mechanics, and beyond.
Copyright:
2026

Book Details

Book Quality:
Publisher Quality
Book Size:
182 Pages
ISBN-13:
9781040634059
Related ISBNs:
9781032847146, 9781003515302, 9781040523803
Publisher:
CRC Press
Date of Addition:
Copyrighted By:
Agnieszka Niemczynowicz, Irina Perfilieva, Lluís M. García-Raffi, and Radosław Kycia
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet, Mathematics and Statistics
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.

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