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A Mathematical Introduction to Compressive Sensing / / by Simon Foucart, Holger Rauhut



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Autore: Foucart Simon Visualizza persona
Titolo: A Mathematical Introduction to Compressive Sensing / / by Simon Foucart, Holger Rauhut Visualizza cluster
Pubblicazione: New York, NY : , : Springer New York : , : Imprint : Birkhäuser, , 2013
Edizione: 1st ed. 2013.
Descrizione fisica: 1 online resource (634 p.)
Disciplina: 621.3822
Soggetto topico: Computer science - Mathematics
Signal processing
Image processing
Speech processing systems
Computer science—Mathematics
Electrical engineering
Functional analysis
Computational Science and Engineering
Signal, Image and Speech Processing
Math Applications in Computer Science
Communications Engineering, Networks
Functional Analysis
Persona (resp. second.): RauhutHolger
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references and index.
Nota di contenuto: 1 An Invitation to Compressive Sensing -- 2 Sparse Solutions of Underdetermined Systems -- 3 Basic Algorithms -- 4 Basis Pursuit -- 5 Coherence -- 6 Restricted Isometry Property -- 7 Basic Tools from Probability Theory -- 8 Advanced Tools from Probability Theory -- 9 Sparse Recovery with Random Matrices -- 10 Gelfand Widths of l1-Balls -- 11 Instance Optimality and Quotient Property -- 12 Random Sampling in Bounded Orthonormal Systems -- 13 Lossless Expanders in Compressive Sensing -- 14 Recovery of Random Signals using Deterministic Matrices -- 15 Algorithms for l1-Minimization -- Appendix A Matrix Analysis -- Appendix B Convex Analysis -- Appendix C Miscellanea -- List of Symbols -- References.
Sommario/riassunto: At the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domains. In the areas of applied mathematics, electrical engineering, and theoretical computer science, an explosion of research activity has already followed the theoretical results that highlighted the efficiency of the basic principles. The elegant ideas behind these principles are also of independent interest to pure mathematicians. A Mathematical Introduction to Compressive Sensing gives a detailed account of the core theory upon which the field is build. Key features include: · The first textbook completely devoted to the topic of compressive sensing · Comprehensive treatment of the subject, including background material from probability theory, detailed proofs of the main theorems, and an outline of possible applications · Numerous exercises designed to help students understand the material · An extensive bibliography with over 500 references that guide researchers through the literature With only moderate prerequisites, A Mathematical Introduction to Compressive Sensing is an excellent textbook for graduate courses in mathematics, engineering, and computer science. It also serves as a reliable resource for practitioners and researchers in these disciplines who want to acquire a careful understanding of the subject.
Titolo autorizzato: A Mathematical Introduction to Compressive Sensing  Visualizza cluster
ISBN: 0-8176-4948-4
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910438034003321
Lo trovi qui: Univ. Federico II
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Serie: Applied and Numerical Harmonic Analysis, . 2296-5009