Sampling theory, a renaissance : compressive sensing and other developments /

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Bibliographic Details
Imprint:Cham : Birkhäuser, [2015].
©2016
Description:1 online resource (xiv, 532 pages) : illustrations (some color).
Language:English
Series:Applied and numerical harmonic analysis, 2296-5009
Applied and numerical harmonic analysis.
Subject:Sampling (Statistics)
Mathematical statistics.
Compressed sensing (Telecommunication) -- Statistical methods.
MATHEMATICS / Applied
MATHEMATICS / Probability & Statistics / General
Mathematical statistics.
Sampling (Statistics)
Electronic books.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11096875
Hidden Bibliographic Details
Other authors / contributors:Pfander, Götz E., editor.
ISBN:9783319197494
3319197495
9783319197487
3319197487
Digital file characteristics:text file PDF
Notes:Includes index.
Online resource; title from PDF title page (SpringerLink, viewed December 21, 2015).
Summary:Reconstructing or approximating objects from seemingly incomplete information is a frequent challenge in mathematics, science, and engineering. A multitude of tools designed to recover hidden information are based on Shannon?s classical sampling theorem, a central pillar of Sampling Theory. The growing need to efficiently obtain precise and tailored digital representations of complex objects and phenomena requires the maturation of available tools in Sampling Theory as well as the development of complementary, novel mathematical theories. Today, research themes such as Compressed Sensing and Frame Theory re-energize the broad area of Sampling Theory. This volume illustrates the renaissance that the area of Sampling Theory is currently experiencing. It touches upon trendsetting areas such as Compressed Sensing, Finite Frames, Parametric Partial Differential Equations, Quantization, Finite Rate of Innovation, System Theory, as well as sampling in Geometry and Algebraic Topology.
Other form:Original 9783319197487 3319197487
Standard no.:10.1007/978-3-319-19749-4
Table of Contents:
  • Part I: Sparsity Models
  • Estimation in High Dimensions: A Geometric Perspective
  • Convex Recovery of a Structured Signal from Independent Random Linear Measurements
  • Low Complexity Regularization of Linear Inverse Problems
  • Part II: Frames with Benefits
  • Noise-shaping Quantization Methods for Frame-based and Compressive Sampling Systems
  • Fourier Operations in Applied Harmonic Analysis.- The Fundamentals of Spectral Tetris Frame Constructions
  • Part III: Bandlimitation Recast
  • System Approximation and Generalized Measurements in Modern Sampling Theory
  • Entire Functions in Generalized Bernstein Spaces and Their Growth Behavior
  • Sampling and Geometry
  • A Sheaf-theoretic Perspective on Sampling
  • Part IV: Solutions of Parametric PDEs
  • How to Best Sample a Solution Manifold?
  • On the Stability of Polynomial Interpolation using Hierarchical Sampling
  • Part V: Implementation
  • OperA: Operator-based Annihilation for Finite-Rate-of-Innovation Signal Sampling
  • Digital Adaptive Calibration of Data Converters using Independent Component Analysis.