03676nam 2200733Ia 450 991078493400332120200520144314.01-282-72302-297866127230253-11-022615-410.1515/9783110226157(CKB)2670000000034670(EBL)570578(OCoLC)659500627(SSID)ssj0000443252(PQKBManifestationID)11267165(PQKBTitleCode)TC0000443252(PQKBWorkID)10455192(PQKB)11733062(MiAaPQ)EBC570578(DE-B1597)38347(OCoLC)979731575(DE-B1597)9783110226157(Au-PeEL)EBL570578(CaPaEBR)ebr10408304(CaONFJC)MIL272302(PPN)202062813(EXLCZ)99267000000003467020100514d2010 uy 0engur|||||||||||txtccrTheoretical foundations and numerical methods for sparse recovery[electronic resource] /edited by Massimo FornasierBerlin ;New York De Gruyterc20101 online resource (350 p.)Radon series on computational and applied mathematics ;9Description based upon print version of record.3-11-022614-6 Includes bibliographical references and index. Frontmatter -- Table of Contents -- Compressive Sensing and Structured Random Matrices -- Numerical Methods for Sparse Recovery -- Sparse Recovery in Inverse Problems -- An Introduction to Total Variation for Image AnalysisThe present collection is the very first contribution of this type in the field of sparse recovery. Compressed sensing is one of the important facets of the broader concept presented in the book, which by now has made connections with other branches such as mathematical imaging, inverse problems, numerical analysis and simulation. The book consists of four lecture notes of courses given at the Summer School on "Theoretical Foundations and Numerical Methods for Sparse Recovery" held at the Johann Radon Institute for Computational and Applied Mathematics in Linz, Austria, in September 2009. This unique collection will be of value for a broad community and may serve as a textbook for graduate courses. From the contents: "Compressive Sensing and Structured Random Matrices" by Holger Rauhut "Numerical Methods for Sparse Recovery" by Massimo Fornasier "Sparse Recovery in Inverse Problems" by Ronny Ramlau and Gerd Teschke "An Introduction to Total Variation for Image Analysis" by Antonin Chambolle, Vicent Caselles, Daniel Cremers, Matteo Novaga and Thomas Pock Radon series on computational and applied mathematics ;9.Sparse matricesEquationsNumerical solutionsDifferential equations, PartialNumerical solutionsImage Processing.Numerical Solution of Partial Differential Inverse Problems.Signal Processing.Sparsity.Sparse matrices.EquationsNumerical solutions.Differential equations, PartialNumerical solutions.512.9/434SK 920SEPArvkFornasier Massimo1541280MiAaPQMiAaPQMiAaPQBOOK9910784934003321Theoretical foundations and numerical methods for sparse recovery3793336UNINA