Photonic Reservoir Computing
Optical Recurrent Neural Networks
Seiten
2019
De Gruyter (Verlag)
978-3-11-058200-0 (ISBN)
De Gruyter (Verlag)
978-3-11-058200-0 (ISBN)
Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.
Daniel Brunner, U Besancon, France; Miguel C. Sariano, U Illes Balears, Spain; Guy Van der Sande, U Brussels, Belgium.
"The book is very clearly written by experts in the field and contains numerous experiments and references. It can be used by anyone working in optical computing, which has developed very much in recent years due to optical implementations of neural networks."
Mircea Dragoman in: OSA. The Optic Society (02.04.2020), https://www.osa-opn.org/home/book_reviews/2020/0420/photonic_reservoir_computing_optical_recurrent_neu/
Erscheinungsdatum | 09.07.2019 |
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Zusatzinfo | 50 b/w and 100 col. ill. |
Verlagsort | Berlin/Boston |
Sprache | englisch |
Maße | 170 x 240 mm |
Gewicht | 666 g |
Themenwelt | Geisteswissenschaften ► Sprach- / Literaturwissenschaft ► Literaturwissenschaft |
Naturwissenschaften ► Physik / Astronomie | |
Schlagworte | Afrika • Computers • electromagnetism • Electromagnetism, Optics and Photonics • Fundamentals of Computer Sciences • Hartmann • Information Theory • Mathematical & Computational • Nanoscience • Optics & Light • Physics • Physik, Astronomie • Science • TECHNOLOGY & ENGINEERING • telecommunications • Tourismus |
ISBN-10 | 3-11-058200-7 / 3110582007 |
ISBN-13 | 978-3-11-058200-0 / 9783110582000 |
Zustand | Neuware |
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