This book will aim to provide a complete treatment of neuromorphic computing spanning from the theoretical to experimental explorations.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Paul R. Prucnal Paul Prucnal is a Professor of Electrical Engineering at Princeton University. In 1988, he joined the faculty at Princeton University, where he served as the Founding Director of Princeton's Center for Photonics and Optoelectronic Materials, and is currently the Director of the Center for Network Science and Applications. He has authored or co-authored more than 350 journal papers and book chapters and holds 22 U.S. patents. He is a Fellow of both the Optical Society of America (OSA) and the Institute of Electrical and Electronics Engineers (IEEE), for his contributions to the field. Bhavin J. Shastri is currently an Associate Research Scholar at Princeton University, Princeton, NJ, USA. His research interests include: beyond-CMOS and More-than-Moore devices; excitable (graphene) lasers; programmable photonic integrated circuits; photonic interconnects; beyond von Neumann architectures; ultrafast cognitive (neuromorphic) computing; photonic spike processing; and high-speed RF circuits. Dr. Shastri is Member of the Institute of Electrical and Electronics Engineers (IEEE) and the Optical Society of America (OSA).
Inhaltsangabe
Neuromorphic Engineering. Primer on Spike Processing and Excitability. Primer on Photonics. Spike Processing with SOA Dynamics. Excitable Laser for Unified Spike Processing. Semiconductor Photonic Devices as Excitable Processors. Silicon Photonics. Weighted Photonic Network Integration. Photonic Weight Banks. Processing-Network Node. System Architecture. Principles of Neural Network Learning. Photonic Reservoir Computing. Neuromorphic Platforms Comparison.
Neuromorphic Engineering. Primer on Spike Processing and Excitability. Primer on Photonics. Spike Processing with SOA Dynamics. Excitable Laser for Unified Spike Processing. Semiconductor Photonic Devices as Excitable Processors. Silicon Photonics. Weighted Photonic Network Integration. Photonic Weight Banks. Processing-Network Node. System Architecture. Principles of Neural Network Learning. Photonic Reservoir Computing. Neuromorphic Platforms Comparison.
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