MARC Record from marc_columbia

LEADER: 04823cam a2200673 i 4500
001 14972567
005 20220423235454.0
006 m o d
007 cr |||||||||||
008 180504s2018 flu ob 001 0 eng
010 $a 2020692009
035 $a(OCoLC)on1193558753
035 $a(NNC)14972567
040 $aDLC$beng$erda$cDLC$dOTZ$dN$T$dYDX$dNLE$dUKMGB$dTYFRS$dMM9$dK6U$dUKAHL$dOCLCO
015 $aGBB8H3750$2bnb
016 7 $a018941281$2Uk
019 $a1044733964$a1052450008$a1073083856$a1171854102$a1289832793
020 $a9781351624145$qebook
020 $a1351624148
020 $z9781138080942$q(hardback)
020 $a9781351624152$q(e-book ;$qPDF)$q(e-book ;$qPDF)
020 $a1351624156
020 $a9781315113142$q(electronic bk.)
020 $a1315113147$q(electronic bk.)
020 $z1138080942
024 7 $a10.1201/9781315113142$2doi
035 $a(OCoLC)1193558753$z(OCoLC)1044733964$z(OCoLC)1052450008$z(OCoLC)1073083856$z(OCoLC)1171854102$z(OCoLC)1289832793
037 $a9781351624145$bIngram Content Group
042 $apcc
050 00 $aQA402.5
072 7 $aBUS$x049000$2bisacsh
072 7 $aBUS$x061000$2bisacsh
072 7 $aMAT$x004000$2bisacsh
072 7 $aPBU$2bicscc
082 00 $a519.6$223
049 $aZCUA
100 1 $aZhao, Yun-Bin,$eauthor.
245 10 $aSparse optimization :$btheory and methods /$cYun-Bin Zhao.
264 1 $aBoca Raton :$bCRC Press, Taylor & Francis Group,$c[2018]
300 $a1 online resource
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
500 $a"A Science Publishers book."
504 $aIncludes bibliographical references and index.
588 $aDescription based on print version record.
505 0 $aChapter 1 Uniqueness of the Sparsest Solution of Linear Systems -- chapter 2 Uniqueness of Solutions to l1-Minimization Problems -- chapter 3 Equivalence of l0- and l1-Minimization -- chapter 1 1-Bit Compressed Sensing -- chapter 5 Stability of Linear Sparse Optimization Methods -- chapter 6 Stability of Nonlinear Sparse Optimization Methods -- chapter 7 Reweighted l1-Algorithms -- chapter 8 Sparsity via Dual Density.
520 3 $aSeeking sparse solutions of underdetermined linear systems is required in many areas of engineering and science such as signal and image processing. The efficient sparse representation becomes central in various big or high-dimensional data processing, yielding fruitful theoretical and realistic results in these fields. The mathematical optimization plays a fundamentally important role in the development of these results and acts as the mainstream numerical algorithms for the sparsity-seeking problems arising from big-data processing, compressed sensing, statistical learning, computer vision, and so on. This has attracted the interest of many researchers at the interface of engineering, mathematics and computer science. Sparse Optimization Theory and Methods presents the state of the art in theory and algorithms for signal recovery under the sparsity assumption. The up-to-date uniqueness conditions for the sparsest solution of underdertemined linear systems are described. The results for sparse signal recovery under the matrix property called range space property (RSP) are introduced, which is a deep and mild condition for the sparse signal to be recovered by convex optimization methods. This framework is generalized to 1-bit compressed sensing, leading to a novel sign recovery theory in this area. Two efficient sparsity-seeking algorithms, reweighted l1-minimization in primal space and the algorithm based on complementary slackness property, are presented. The theoretical efficiency of these algorithms is rigorously analysed in this book. Under the RSP assumption, the author also provides a novel and unified stability analysis for several popular optimization methods for sparse signal recovery, including l1-mininization, Dantzig selector and LASSO. This book incorporates recent development and the author's latest research in the field that have not appeared in other books.
650 0 $aMathematical optimization.
650 6 $aOptimisation mathématique.
650 7 $aMATHEMATICS$xApplied.$2bisacsh
650 7 $aMATHEMATICS$xProbability & Statistics$xGeneral.$2bisacsh
650 7 $aLasso.$2fast$0(OCoLC)fst00992930
650 7 $aMathematical optimization.$2fast$0(OCoLC)fst01012099
655 0 $aElectronic books.
655 4 $aElectronic books.
776 08 $iPrint version:$tSparse optimization$dBoca Raton, FL : CRC Press, Taylor & Francis Group, [2018]$z9781138080942$w(DLC) 2018014321
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio14972567$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS