Compressed Sensing in Li-Fi and Wi-Fi Networks

Nonfiction, Science & Nature, Technology, Engineering, Computers, General Computing
Cover of the book Compressed Sensing in Li-Fi and Wi-Fi Networks by Malek Benslama, Hatem Mokhtari, Elsevier Science
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Author: Malek Benslama, Hatem Mokhtari ISBN: 9780081019689
Publisher: Elsevier Science Publication: November 20, 2017
Imprint: ISTE Press - Elsevier Language: English
Author: Malek Benslama, Hatem Mokhtari
ISBN: 9780081019689
Publisher: Elsevier Science
Publication: November 20, 2017
Imprint: ISTE Press - Elsevier
Language: English

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
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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.

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