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082 0 4 _a621.382
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100 1 _aWang, Xueqian.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aStudy on Signal Detection and Recovery Methods with Joint Sparsity
_h[electronic resource] /
_cby Xueqian Wang.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXVI, 121 p. 52 illus., 36 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _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.
541 _fUABC ;
_cPerpetuidad
650 0 _aSignal processing.
650 1 4 _aSignal, Speech and Image Processing.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819941162
776 0 8 _iPrinted edition:
_z9789819941186
776 0 8 _iPrinted edition:
_z9789819941193
830 0 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5061
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-99-4117-9
912 _aZDB-2-ENG
912 _aZDB-2-SXE
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