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008			230930s2024 si | fo |||| 0|eng d
020			_a9789819941179
024	7		_a10.1007/978-981-99-4117-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5102.9 _b2024 EB
100	1		_aWang, Xueqian _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9690347
245	1	0	_aStudy on Signal Detection and Recovery Methods with Joint Sparsity _cby Xueqian Wang
250			_a1st ed. 2024
264		1	_aSingapore _bSpringer International Publishing _c2024
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aSpringer Theses, Recognizing Outstanding Ph.D. Research _x2190-5061
505	0		_aIntroduction -- Joint Sparse Signal Detection Based On Locally Most Powerful Test Under Gaussian Model -- Joint Sparse Signal Detection Based On Locally Most Powerful Test Under Generalized Gaussian Model -- Joint Sparse Signal Recovery Based On Look-Ahead Selection of Basis-Signals -- Joint Sparse Signal Recovery Based On Two-Level Sparsity -- Summary and Outlook. .
520			_aThe task of signal detection is deciding whether signals of interest exist by using their observed data. Furthermore, signals are reconstructed or their key parameters are estimated from the observations in the task of signal recovery. Sparsity is a natural characteristic of most of signals in practice. The fact that multiple sparse signals share the common locations of dominant coefficients is called by joint sparsity. In the context of signal processing, joint sparsity model results in higher performance of signal detection and recovery. This book focuses on the task of detecting and reconstructing signals with joint sparsity. The main contents include key methods for detection of joint sparse signals and their corresponding theoretical performance analysis, and methods for joint sparse signal recovery and their application in the context of radar imaging.
988			_aSpringer_Engineering_2024
650		7	_2embne _9150608 _aProceso de señales
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-99-4117-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2024 _dz _eb _zSI