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The Resource A Mathematical Introduction to Compressive Sensing, by Simon Foucart, Holger Rauhut, (electronic resource)
A Mathematical Introduction to Compressive Sensing, by Simon Foucart, Holger Rauhut, (electronic resource)
Resource Information
The item A Mathematical Introduction to Compressive Sensing, by Simon Foucart, Holger Rauhut, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Oklahoma Libraries.This item is available to borrow from all library branches.
Resource Information
The item A Mathematical Introduction to Compressive Sensing, by Simon Foucart, Holger Rauhut, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Oklahoma Libraries.
This item is available to borrow from all library branches.
 Summary
 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
 Language

 eng
 eng
 Edition
 1st ed. 2013.
 Extent
 1 online resource (634 p.)
 Note
 Description based upon print version of record
 Contents

 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 l1Balls
 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 l1Minimization
 Appendix A Matrix Analysis
 Appendix B Convex Analysis
 Appendix C Miscellanea
 List of Symbols
 References
 Isbn
 9780817649487
 Label
 A Mathematical Introduction to Compressive Sensing
 Title
 A Mathematical Introduction to Compressive Sensing
 Statement of responsibility
 by Simon Foucart, Holger Rauhut
 Language

 eng
 eng
 Summary
 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
 http://library.link/vocab/creatorName
 Foucart, Simon
 Dewey number

 621.382
 621.3822
 http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut

 5lGAiWXjAKI
 ADw55yroiE8
 Language note
 English
 LC call number
 QA7190
 Literary form
 non fiction
 Nature of contents
 dictionaries
 http://library.link/vocab/relatedWorkOrContributorName
 Rauhut, Holger.
 Series statement
 Applied and Numerical Harmonic Analysis,
 http://library.link/vocab/subjectName

 Computer science
 Telecommunication
 Functional analysis
 Computational Science and Engineering
 Signal, Image and Speech Processing
 Math Applications in Computer Science
 Communications Engineering, Networks
 Functional Analysis
 Label
 A Mathematical Introduction to Compressive Sensing, by Simon Foucart, Holger Rauhut, (electronic resource)
 Note
 Description based upon print version of record
 Carrier category
 online resource
 Carrier category code
 cr
 Content category
 text
 Content type code
 txt
 Contents
 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 l1Balls  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 l1Minimization  Appendix A Matrix Analysis  Appendix B Convex Analysis  Appendix C Miscellanea  List of Symbols  References
 Dimensions
 unknown
 Edition
 1st ed. 2013.
 Extent
 1 online resource (634 p.)
 Form of item
 online
 Isbn
 9780817649487
 Media category
 computer
 Media type code
 c
 Other control number
 10.1007/9780817649487
 Specific material designation
 remote
 System control number

 (CKB)3710000000015694
 (EBL)1387199
 (OCoLC)870244277
 (SSID)ssj0000988209
 (PQKBManifestationID)11572618
 (PQKBTitleCode)TC0000988209
 (PQKBWorkID)10950651
 (PQKB)11188012
 (DEHe213)9780817649487
 (EXLCZ)993710000000015694
 Label
 A Mathematical Introduction to Compressive Sensing, by Simon Foucart, Holger Rauhut, (electronic resource)
 Note
 Description based upon print version of record
 Carrier category
 online resource
 Carrier category code
 cr
 Content category
 text
 Content type code
 txt
 Contents
 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 l1Balls  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 l1Minimization  Appendix A Matrix Analysis  Appendix B Convex Analysis  Appendix C Miscellanea  List of Symbols  References
 Dimensions
 unknown
 Edition
 1st ed. 2013.
 Extent
 1 online resource (634 p.)
 Form of item
 online
 Isbn
 9780817649487
 Media category
 computer
 Media type code
 c
 Other control number
 10.1007/9780817649487
 Specific material designation
 remote
 System control number

 (CKB)3710000000015694
 (EBL)1387199
 (OCoLC)870244277
 (SSID)ssj0000988209
 (PQKBManifestationID)11572618
 (PQKBTitleCode)TC0000988209
 (PQKBWorkID)10950651
 (PQKB)11188012
 (DEHe213)9780817649487
 (EXLCZ)993710000000015694
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Architecture LibraryBorrow itGould Hall 830 Van Vleet Oval Rm. 105, Norman, OK, 73019, US35.205706 97.445050



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Engineering LibraryBorrow itFelgar Hall 865 Asp Avenue, Rm. 222, Norman, OK, 73019, US35.205706 97.445050

Fine Arts LibraryBorrow itCatlett Music Center 500 West Boyd Street, Rm. 20, Norman, OK, 73019, US35.210371 97.448244

Harry W. Bass Business History CollectionBorrow it401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US35.207487 97.447906

History of Science CollectionsBorrow it401 W. Brooks St., Rm. 521NW, Norman, OK, 73019, US35.207487 97.447906

John and Mary Nichols Rare Books and Special CollectionsBorrow it401 W. Brooks St., Rm. 509NW, Norman, OK, 73019, US35.207487 97.447906


Price College Digital LibraryBorrow itAdams Hall 102 307 West Brooks St., Norman, OK, 73019, US35.210371 97.448244

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