000			03093nam a2200457 c 4500
710	2		_aSpringerLink (Online service) _9106996
999			_c118160 _d118160
001			118160
003			ES-MaUEC
005			20230102113846.0
006			a||||fo|||| 00| 0
007			cr nn nnnaamaa
008			191027s2019 gw a o |||| 0|eng d
020			_a9783030156008
024	7		_a10.1007/978-3-030-15600-8 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK7871.6 _b2019 EB
100	1		_aBenesty, Jacob _9673239
245	1	0	_aArray Processing : _bKronecker Product Beamforming _cby Jacob Benesty, Israel Cohen, Jingdong Chen
250			_aPrimera edición 2019
264		1	_aCham _bSpringer _c2019
300			_a1 recurso en línea (XI, 189 páginas) _b 1 ilustraciones
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aSpringer Topics in Signal Processing _x1866-2609 _v18
505	0		_aIntroduction -- Problem Formulation with Uniform Linear Arrays -- Beamforming with Uniform Linear Arrays -- Generalization with Uniform Linear Arrays -- Approach with Nonuniform Linear Arrays -- Approach with Rectangular Arrays -- Spatiotemporal Signal Enhancement.
520	3		_aThe focus of this book is on array processing and beamforming with Kronecker products. It considers a large family of sensor arrays that allow the steering vector to be decomposed as a Kronecker product of two steering vectors of smaller virtual arrays. Instead of directly designing a global beamformer for the original array, once the steering vector has been decomposed, smaller virtual beamformers are designed and separately optimized for each virtual array. This means the matrices that need to be inverted are smaller, which increases the robustness of the beamformers, and reduces the size of the observations. The book explains how to perform beamforming with Kronecker product filters using an unconventional approach. It shows how the Kronecker product formulation can be used to derive fixed, adaptive, and differential beamformers with remarkable flexibility. Furthermore, it demonstrates how fixed and adaptive beamformers can be intelligently combined, optimally exploiting the advantages of both. The problem of spatiotemporal signal enhancement is also addressed, and readers will learn how to perform Kronecker product filtering in this context.
988			_aPrimersemestre_2020_Engineering
650		7	_2embne _aAntenas _9138526
700	1		_aCohen, Israel. _eautor
700	1		_aChen, Jingdong _eautor _9100906
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783030155995
776	0	8	_iPrinted edition: _z9783030156015
776	0	8	_iPrinted edition: _z9783030156022
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-15600-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b04/2020 _dz _eu _zSI