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Elsevier Compressed Sensing in Li-Fi and Wi-Fi Networks

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Description

Compressed Sensing in Li-Fi and Wi-Fi Networks features coverage of the first applications in optical telecommunications and wireless. After extensive development of basic theory, many techniques are presented, such as non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and the use of graphical models. The book can be used as a comprehensive manual for teaching and research in courses covering advanced signal processing, efficient data processing algorithms, and telecommunications. After a thorough review of the basic theory of compressed sensing, many mathematical techniques are presented, including advanced signal modeling, Nyquist sub-sampling of analog signals, the non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and the use of graphical models. Offers extensive development of basic theory behind telecommunications and wireless networks Contains broad coverage of treat compressed sensing, including electromagnetism signals Provides insights into the two key areas of telecommunications, WIFI and LIFI Includes information on advanced signal modeling, Nyquist sub-sampling of analog signals, the non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and more Review This comprehensive manual covers everything from basic theory of compressed sensing to advanced signal processing and efficient data processing algorithms About the Author Malek Benslama is currently Professor at the University of Constantine 1 in Algeria. He is also Doctor of Science with the INP Toulouse in France and a member of the scientific council of the Algerian Space Agency. Hatem Mokhtari was formerly Lecturer at the University of Constantine 1 in Algeria. He currently provides consulting services on an international scale for telecommunications and holds a doctorate from Paul Verlaine University - Metz in France.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
20 November 2017
Listed Since
27 July 2016

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