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In den Warenkorbpaperback. Zustand: Very Good. Non-Orthogonal Multiple Access for Massive Connectivity (SpringerBriefs in Computer Science) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
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Sprache: Englisch
Verlag: Cham, Springer International Publishing., 2019
ISBN 10: 3030063607 ISBN 13: 9783030063603
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24 cm. XXIII, 685 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch.
Zustand: New. pp. XIV, 101 26 illus., 25 illus. in color. 1 Edition NO-PA16APR2015-KAP.
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Sprache: Englisch
Verlag: The Institution of Engineering and Technology, 2019
ISBN 10: 1785616579 ISBN 13: 9781785616570
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Hardback. Zustand: New. Machine learning explores the study and development of algorithms that can learn from and make predictions and decisions based on data. Applications of machine learning in wireless communications have been receiving a lot of attention, especially in the era of big data and IoT, where data mining and data analysis technologies are effective approaches to solving wireless system evaluation and design issues. This edited book presents current and future developments and trends in wireless communication technologies based on contributions from machine learning and other fields of artificial intelligence, including channel modelling, signal estimation and detection, energy efficiency, cognitive radios, wireless sensor networks, vehicular communications, and wireless multimedia communications. The book is aimed at a readership of researchers, engineers and students working on wireless communications and machine learning, especially those working with big data and artificial intelligence multi-disciplinary fields related to wireless communication technologies.
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Verlag: The Institution of Engineering and Technology, 2019
ISBN 10: 1785616579 ISBN 13: 9781785616570
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Verlag: The Institution of Engineering and Technology, 2019
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Verlag: Springer-Nature New York Inc, 2026
ISBN 10: 3032095506 ISBN 13: 9783032095503
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In den WarenkorbZustand: New. Yuanwei Liu, PhD, is a Senior Lecturer (Associate Professor) with the School of Electronic Engineering and Computer Science at Queen Mary University of London, UK.Liang Liu, PhD, is an Assistant Professor in the Department of Electrical and Electronic Engin.
Sprache: Englisch
Verlag: Institution of Engineering and Technology, GB, 2019
ISBN 10: 1785616579 ISBN 13: 9781785616570
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In den WarenkorbHardback. Zustand: New. Machine learning explores the study and development of algorithms that can learn from and make predictions and decisions based on data. Applications of machine learning in wireless communications have been receiving a lot of attention, especially in the era of big data and IoT, where data mining and data analysis technologies are effective approaches to solving wireless system evaluation and design issues. This edited book presents current and future developments and trends in wireless communication technologies based on contributions from machine learning and other fields of artificial intelligence, including channel modelling, signal estimation and detection, energy efficiency, cognitive radios, wireless sensor networks, vehicular communications, and wireless multimedia communications. The book is aimed at a readership of researchers, engineers and students working on wireless communications and machine learning, especially those working with big data and artificial intelligence multi-disciplinary fields related to wireless communication technologies.
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In den WarenkorbHardcover. Zustand: Brand New. 624 pages. 9.00x6.00x0.06 inches. In Stock.
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