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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Daniel Brunner, U Besancon, France; Miguel C. Sariano, U Illes Balears, Spain; Guy Van der Sande, U Brussels, Belgium.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 network. N° de réf. du vendeur 218771050
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783110582000
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 276 pp. Englisch. N° de réf. du vendeur 9783110582000
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Buch. Etat : Neu. Neuware -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.Walter de Gruyter, Genthiner Straße 13, 10785 Berlin 276 pp. Englisch. N° de réf. du vendeur 9783110582000
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Hardback. Etat : New. 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. N° de réf. du vendeur LU-9783110582000
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