000 02374nam a22003618i 4500
001 CR9780511804458
003 UkCbUP
005 20200124160315.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 101021s2010||||enk o ||1 0|eng|d
020 _a9780511804458 (ebook)
020 _z9780521762229 (hardback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aTK5102.9
_b.C587 2010
082 0 4 _a621.3822015196
_222
245 0 0 _aConvex optimization in signal processing and communications /
_cedited by Daniel P. Palomar and Yonina C. Eldar.
246 3 _aConvex Optimization in Signal Processing & Communications
264 1 _aCambridge :
_bCambridge University Press,
_c2010.
300 _a1 online resource (xiv, 498 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520 _aOver the past two decades there have been significant advances in the field of optimization. In particular, convex optimization has emerged as a powerful signal processing tool, and the variety of applications continues to grow rapidly. This book, written by a team of leading experts, sets out the theoretical underpinnings of the subject and provides tutorials on a wide range of convex optimization applications. Emphasis throughout is on cutting-edge research and on formulating problems in convex form, making this an ideal textbook for advanced graduate courses and a useful self-study guide. Topics covered range from automatic code generation, graphical models, and gradient-based algorithms for signal recovery, to semidefinite programming (SDP) relaxation and radar waveform design via SDP. It also includes blind source separation for image processing, robust broadband beamforming, distributed multi-agent optimization for networked systems, cognitive radio systems via game theory, and the variational inequality approach for Nash equilibrium solutions.
650 0 _aSignal processing.
650 0 _aMathematical optimization.
650 0 _aConvex functions.
700 1 _aPalomar, Daniel P.,
_eeditor.
700 1 _aEldar, Yonina C.,
_eeditor.
776 0 8 _iPrint version:
_z9780521762229
856 4 0 _uhttps://doi.org/10.1017/CBO9780511804458
999 _c521350
_d521348