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008			150529s2015 si | s |||| 0|eng d
020			_a9789812873903
024	7		_a10.1007/978-981-287-390-3 _2doi
040			_bspa _dES-MaUEC
050		4	_aTK7872.D48 _b2015 EB
100	1		_aColuccia, Giulio. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/307335455/
245	1	0	_aCompressed Sensing for Distributed Systems _cby Giulio Coluccia, Chiara Ravazzi, Enrico Magli.
264		1	_aSingapore _bSpringer International Publishing _c2015
300			_a1 recurso en línea (X, 97 páginas 23 ilustraciones, 14 ilustraciones a color.)
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
490	0		_aSpringerBriefs in Signal Processing, _x2196-4076
490	0		_aEngineering (Springer-11647)
505	0		_aIntroduction -- Distributed Compressed Sensing -- Rate-Distortion Theory of Distributed Compressed Sensing -- Centralized Joint Recovery -- Distributed Recovery -- Conclusions.
520	3		_aThis book presents a survey of the state-of-the art in the exciting and timely topic of compressed sensing for distributed systems. It has to be noted that, while compressed sensing has been studied for some time now, its distributed applications are relatively new. Remarkably, such applications are ideally suited to exploit all the benefits that compressed sensing can provide. The objective of this book is to provide the reader with a comprehensive survey of this topic, from the basic concepts to different classes of centralized and distributed reconstruction algorithms, as well as a comparison of these techniques. This book collects different contributions on these aspects. It presents the underlying theory in a complete and unified way for the first time, presenting various signal models and their use cases. It contains a theoretical part collecting latest results in rate-distortion analysis of distributed compressed sensing, as well as practical implementations of algorithms obtaining performance close to the theoretical bounds. It presents and discusses various distributed reconstruction algorithms, summarizing the theoretical reconstruction guarantees and providing a comparative analysis of their performance and complexity. In summary, this book will allow the reader to get started in the field of distributed compressed sensing from theory to practice. We believe that this book can find a broad audience among researchers, scientists, or engineers with very diverse backgrounds, having interests in mathematical optimization, network systems, graph theoretical methods, linear systems, stochastic systems, and randomized algorithms. To help the reader become familiar with the theory and algorithms presented, accompanying software is made available on the authors' web site, implementing several of the algorithms described in the book. The only background required of the reader is a good knowledge of advanced calculus and linear algebra.
988			_aEBSPRINGER_2018
650		7	_aRedes de sensores inalámbricas _2embne _9441179
700	1		_aRavazzi, Chiara. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/nb2015015125 _1http://viaf.org/viaf/317284711/
700	1		_aMagli, Enrico. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/313563980/
776	0	8	_iEdición impresa: _z9789812873910
776	0	8	_iEdición impresa: _z9789812873897
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-287-390-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2019 _dz _eIG _zSI