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	Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications - ISBN 9781498776455

Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications

ISBN 9781498776455

Autor: Chong-Yung Chi

Wydawca: CRC Press

Dostępność: Wysyłka w ciągu 2-3 dni

Cena: 589,05 zł


ISBN13:      

9781498776455

ISBN10:      

1498776450

Autor:      

Chong-Yung Chi

Oprawa:      

Hardback

Rok Wydania:      

2017-02-09

Ilość stron:      

432

Tematy:      


Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications provides fundamental background knowledge of convex optimization, while striking a balance between mathematical theory and applications in signal processing and communications. In addition to comprehensive proofs and perspective interpretations for core convex optimization theory, this book also provides many insightful figures, remarks, illustrative examples, and guided journeys from theory to cutting-edge research explorations, for efficient and in-depth learning, especially for engineering students and professionals. With the powerful convex optimization theory and tools, this book provides you with a new degree of freedom and the capability of solving challenging real-world scientific and engineering problems.

Author Biography: Dr. Chong-Yung Chi is a Professor, Department of Electrical Engineering (since 1989) and the Institute of Communications Engineering, National Tsing Hua University, Hsinchu, Taiwan. He got his Ph.D. degree in Electrical Engineering from University of Southern California in 1983.His main research interests include signal processing for wireless communications, convex analysis and optimization for blind source separation, biomedical and hyperspectral image analysis. He has published more than 210 technical papers, including more than 75 journal papers (mostly in IEEE Trans. Signal Processing), 4 book chapters and more than 130 peer-reviewed conference papers, as well as a graduate-level textbook, Blind Equalization and System Identification, Springer-Verlag, 2006. Dr. Chi is a senior member of IEEE. He was an Associate Editor (AE) of IEEE Trans. Signal Processing (5/2001~4/2006), IEEE Trans. Circuits and Systems II (1/2006-12/2007), IEEE Trans. Circuits and Systems I (1/2008-12/2009), AE of IEEE Signal Processing Letters (6/2006~5/2010), and a member of Editorial Board of Elsevier Signal Processing (6/2005~5/2008), and an editor (7/2003~12/2005) as well as a Guest Editor (2006) of EURASIP Journal on Applied Signal Processing. Currently, he is a member of Signal Processing for Communications and Networking Technical Committee (SPCOM-TC) and a member of Sensor Array and Multichannel Technical Committee (SAM-TC), IEEE Signal Processing Society, and an AE of IEEE Trans. Signal Processing. Wei-Chiang Li received the B.S. degree in electrical engineering from the National Tsing Hua University, Hsinchu, Taiwan, in 2009. He is currently pursuing the Ph.D. degree in communications engineering at the National Tsing Hua University, Hsinchu, Taiwan. His research interests are in optimization methods for wireless communications and signal processing. Chia-Hsiang Lin received the B.S. degree in electrical engineering from the National Tsing Hua University, Hsinchu, Taiwan, in 2010, where he is currently working toward the Ph.D. degree in communications engineering. He is currently a visiting Doctoral Graduate Research Assistant with Virginia Polytechnic Institute and State University, Arlington, VA, USA. His research interests are convex geometry and optimization, network science, game theory, and blind source separation.

Preface Chapter 1: Mathematical Background Chapter 2: Convex Sets Chapter 3: Convex Functions Chapter 4: Convex Optimization Problems Chapter 5: Geometric Programming Chapter 6: Linear Programming and Quadratic Programming Chapter 7: Second-order Cone Programming Chapter 8: Semidefinite Programming Chapter 9: Duality Chapter 10: Interior-point Methods Appendix: Convex Optimization Solvers

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