Selected aspects of complex, hypercomplex and fuzzy neural networks

Autor:	Niemczynowicz, Agnieszka, Kycia, Radosław A., Jaworski, Maciej, Siemaszko, Artur, Calabuig, Jose M., García-Raffi, Lluis M., Schneider, Baruch, Berseghyan, Diana, Perfiljeva, Irina, Novak, Vilem, Artiemjew, Piotr
Rok vydání:	2022
Předmět:	Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	This short report reviews the current state of the research and methodology on theoretical and practical aspects of Artificial Neural Networks (ANN). It was prepared to gather state-of-the-art knowledge needed to construct complex, hypercomplex and fuzzy neural networks. The report reflects the individual interests of the authors and, by now means, cannot be treated as a comprehensive review of the ANN discipline. Considering the fast development of this field, it is currently impossible to do a detailed review of a considerable number of pages. The report is an outcome of the Project 'The Strategic Research Partnership for the mathematical aspects of complex, hypercomplex and fuzzy neural networks' meeting at the University of Warmia and Mazury in Olsztyn, Poland, organized in September 2022. Comment: 46 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2301.00007 Zobrazit plný text záznamu View this record from Arxiv