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Application of FPGA to Real-Time Machine Learning: Hardware Reservoir Computers and Software Image P
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Application of FPGA to Real-Time Machine Learning: Hardware Reservoir Computers and Software Image P

Application of FPGA to Real-Time Machine Learning: Hardware Reservoir Computers and Software Image P

Piotr Antonik

171 pages, parution le 30/05/2018

Résumé

This book lies at the interface of machine learning - a subfield of computer science that develops algorithms for challenging tasks such as shape or image recognition, where traditional algorithms fail - and photonics - the physical science of light, which underlies many of the optical communications technologies used in our information society. It provides a thorough introduction to reservoir computing and field-programmable gate arrays (FPGAs).pPiotr Antonik was born in 1989 in Minsk, Belarus. He received his Master's degree and his PhD in physics from the Universite libre de Bruxelles, Brussels, Belgium, in 2013 and 2017, respectively. He is currently a post-doctoral researcher at the LMOPS Lab, CentraleSupelec, Metz, France. His research interests include spatial and time-delay photonic implementations of reservoir computing, FPGA programming, online learning methods, and applications of machine learning to biomedical imaging.

Caractéristiques techniques

  PAPIER
Éditeur(s) Springer
Auteur(s) Piotr Antonik
Parution 30/05/2018
Nb. de pages 171
EAN13 9783319910529

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