How can machine learning help the design of future communication networks – and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications – an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge.
"Sinopsis" puede pertenecer a otra edición de este libro.
Yonina C. Eldar is a professor of Electrical Engineering at the Weizmann Institute of Science, where she heads the Center for Biomedical Engineering and Signal Processing. She is also a visiting professor at MIT and at the Broad Institute, and an adjunct professor at Duke University. She is a member of the Israel Academy of Sciences and Humanities, an IEEE fellow, and a EURASIP fellow.
Andrea Goldsmith is the Dean of Engineering and Applied Science and the Arthur LeGrand Doty Professor of Electrical Engineering at Princeton University. She is a member of the US National Academy of Engineering and the American Academy of Arts and Sciences. In 2020, she received the Marconi Prize.
Deniz Gündüz is a professor of Information Processing in the Electrical and Electronic Engineering Department of Imperial College London in the UK, where he serves as the Deputy Head of the Intelligent Systems and Networks Group. He is also a part-time faculty member at the University of Modena and Reggio Emilia in Italy.
H. Vincent Poor is the Michael Henry Strater University Professor at Princeton University. He is a member of the US National Academy of Engineering and the US National Academy of Sciences. In 2017, he received the IEEE Alexander Graham Bell Medal.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: Prior Books Ltd, Cheltenham, Reino Unido
Hardcover. Condición: Like New. First Edition. Hardback book in nearly new condition: firm and square with strong joints. Just a few hardly noticeable rubs or very mild bumps. Hence a non-text page shows a small 'damaged' stamp. Despite such this book looks and feels unread. Thus the contents are crisp, fresh and tight. And so a very nice book in great condition, now offered for sale at a reasonable price. Nº de ref. del artículo: 203592
Cantidad disponible: 1 disponibles
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 44203399-n
Cantidad disponible: 1 disponibles
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Hardcover. Condición: new. Hardcover. How can machine learning help the design of future communication networks and how can future networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most transformative and impactful technologies of our age in this comprehensive book. First, learn how modern machine learning techniques, such as deep neural networks, can transform how we design and optimize future communication networks. Accessible introductions to concepts and tools are accompanied by numerous real-world examples, showing you how these techniques can be used to tackle longstanding problems. Next, explore the design of wireless networks as platforms for machine learning applications an overview of modern machine learning techniques and communication protocols will help you to understand the challenges, while new methods and design approaches will be presented to handle wireless channel impairments such as noise and interference, to meet the demands of emerging machine learning applications at the wireless edge. How can machine learning help the design of future communication networks? How can future wireless networks meet the demands of emerging machine learning applications? Discover the interactions between two of the most impactful technologies of our age in this comprehensive book, with accessible introductions and real-world examples. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781108832984
Cantidad disponible: 1 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Nº de ref. del artículo: I-9781108832984
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 44203399
Cantidad disponible: 1 disponibles
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In. Nº de ref. del artículo: ria9781108832984_new
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: New. Nº de ref. del artículo: 44203399-n
Cantidad disponible: 1 disponibles
Librería: Revaluation Books, Exeter, Reino Unido
Hardcover. Condición: Brand New. 575 pages. 9.75x6.75x1.25 inches. In Stock. Nº de ref. del artículo: __1108832989
Cantidad disponible: 1 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 44203399
Cantidad disponible: 1 disponibles
Librería: Russell Books, Victoria, BC, Canada
hardcover. Condición: New. New. Special order direct from the distributor. Nº de ref. del artículo: ING9781108832984
Cantidad disponible: 1 disponibles