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OverviewPhotonics 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. Full Product DetailsAuthor: Daniel Brunner , Miguel C. Soriano , Guy Van der SandePublisher: De Gruyter Imprint: De Gruyter Dimensions: Width: 17.00cm , Height: 2.00cm , Length: 24.00cm Weight: 0.666kg ISBN: 9783110582000ISBN 10: 3110582007 Pages: 277 Publication Date: 08 July 2019 Audience: Professional and scholarly , Professional & Vocational , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsThe 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/ 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/ Author InformationDaniel Brunner, U Besancon, France; Miguel C. Sariano, U Illes Balears, Spain; Guy Van der Sande, U Brussels, Belgium. Tab Content 6Author Website:Countries AvailableAll regions |