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Sampling Theory, a Renaissance

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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 3: Low Complexity Regularization of Linear Inverse Problems
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