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Sampling Theory, a Renaissance

Overview of attention for book
Cover of 'Sampling Theory, a Renaissance'

Table of Contents

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    Book Overview
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    Chapter 1 Estimation in High Dimensions: A Geometric Perspective
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    Chapter 2 Convex Recovery of a Structured Signal from Independent Random Linear Measurements
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    Chapter 3 Low Complexity Regularization of Linear Inverse Problems
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    Chapter 4 Noise-Shaping Quantization Methods for Frame-Based and Compressive Sampling Systems
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    Chapter 5 Fourier Operators in Applied Harmonic Analysis
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    Chapter 6 The Fundamentals of Spectral Tetris Frame Constructions
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    Chapter 7 System Approximations and Generalized Measurements in Modern Sampling Theory
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    Chapter 8 Entire Functions in Generalized Bernstein Spaces and Their Growth Behavior
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    Chapter 9 Sampling in Euclidean and Non-Euclidean Domains: A Unified Approach
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    Chapter 10 A Sheaf-Theoretic Perspective on Sampling
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    Chapter 11 How To Best Sample a Solution Manifold?
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    Chapter 12 On the Stability of Polynomial Interpolation Using Hierarchical Sampling
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    Chapter 13 OperA: Operator-Based Annihilation for Finite-Rate-of-Innovation Signal Sampling
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    Chapter 14 Digital Adaptive Calibration of Data Converters Using Independent Component Analysis
Attention for Chapter 10: A Sheaf-Theoretic Perspective on Sampling
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Citations

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Chapter title
A Sheaf-Theoretic Perspective on Sampling
Chapter number 10
Book title
Sampling Theory, a Renaissance
Published by
Birkhäuser, Cham, January 2015
DOI 10.1007/978-3-319-19749-4_10
Book ISBNs
978-3-31-919748-7, 978-3-31-919749-4
Authors

Michael Robinson

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Student > Bachelor 2 25%
Researcher 1 13%
Student > Master 1 13%
Unknown 2 25%
Readers by discipline Count As %
Business, Management and Accounting 2 25%
Engineering 2 25%
Computer Science 1 13%
Mathematics 1 13%
Unknown 2 25%

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