Neuromorphic Computing Principles and Organization

Lieferzeit: Lieferbar innerhalb 14 Tagen

85,59 

ISBN: 3031830881
ISBN 13: 9783031830884
Autor: Ben Abdallah, Abderazek/Dang, Khanh N
Verlag: Springer Verlag GmbH
Umfang: xxxi, 307 S., 36 s/w Illustr., 103 farbige Illustr., 307 p. 139 illus., 103 illus. in color.
Erscheinungsdatum: 24.04.2025
Auflage: 2/2025
Produktform: Gebunden/Hardback
Einband: Gebunden
Artikelnummer: 5113367 Kategorie:

Beschreibung

Autorenporträt

Dr. Abderazek Ben Abdallah received his Ph.D. in computer engineering from The University of Electro-Communications in Tokyo in 2002. From April 2014to March 2022, he served as the Head of the Computer Engineering Division at the University of Aizu, Japan. Since April 2022, he has held the position of Dean at the School of Computer Science and Engineering at the University of Aizu. Currently, Dr. Ben Abdallah is a Full Professor at the University of Aizu. He is the author of four books and holds six registered and eight provisional Japanese patents. Additionally, he has published over 150 peer-reviewed journal articles and conference papers. His research interests span adaptive and self-organizing systems, neuromorphic computing, interconnection networks, and AI-powered cyber-physical systems. Dr. Ben Abdallah is a Senior Member of both the IEEE and ACM, reflecting his significant contributions to computer engineering. Dr. Khanh N. Dang currently serves as an Associate Professor in the Department of Computer Science and Engineering at the University of Aizu. He earned his Ph.D. from the University of Aizu and his M.Sc. from the University of Paris XI. Dr. Dang has published numerous peer-reviewed journal articles and presented his work at various conferences. He is also the author of one book and holds several provisional patents in Japan. Dr. Dangs research areas include Network-on-Chips (NoC), 3DIntegrated Circuits (3D-ICs), neuromorphic computing, and fault-tolerant systems. Within these fields, he focuses on developing efficient communication architectures and enhancing the reliability and performance of multi-core processors. In neuromorphic computing, he explores the implementation of brain-inspired algorithms to create more efficient and intelligent systems. He is a member of IEEE.

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