TY  - BOOK
AU  - Eldar,Yonina C.
TI  - Machine Learning and Wireless Communications
SN  - 9781108832984
AV  - TK5103.2 .M315 2022
U1  - 621.382 23/eng/20220318
PY  - 2022///
CY  - Cambridge, United Kingdom, New York, NY
PB  - Cambridge University Press
KW  - Wireless communication systems
KW  - Machine learning
KW  - TECHNOLOGY & ENGINEERING / Signals & Signal Processing
KW  - bisacsh
N1  - Includes bibliographical references and index; Deep neural networks for joint source-channel coding / David Burth Kurka, Milind Rao, Nariman Farsad, Deniz Gündüz, Andrea Goldsmith -- Timely wireless edge inference / Sheng Zhou, Wenqi Shi, Xiufeng Huang, and Zhisheng Niu
N2  - "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"--
ER  -