Chapter 1 A Survey of Compressed Sensing

Chapter 3 Compressed Sensing, Sparse Inversion, and Model Mismatch

Chapter 4 Recovering Structured Signals in Noise: Least-Squares Meets Compressed Sensing

Chapter 5 The Quest for Optimal Sampling: Computationally Efficient, Structure-Exploiting Measurements for Compressed Sensing

Chapter 6 Compressive Sensing in Acoustic Imaging

Chapter 7 Quantization and Compressive Sensing

Chapter 8 Compressive Gaussian Mixture Estimation

Chapter 9 Two Algorithms for Compressed Sensing of Sparse Tensors

Chapter 10 Sparse Model Uncertainties in Compressed Sensing with Application to Convolutions and Sporadic Communication

Chapter 11 Cosparsity in Compressed Sensing

Chapter 12 Structured Sparsity: Discrete and Convex Approaches

Chapter 13 Explicit Matrices with the Restricted Isometry Property: Breaking the Square-Root Bottleneck

Chapter 14 Tensor Completion in Hierarchical Tensor Representations

Chapter 15 Compressive Classification: Where Wireless Communications Meets Machine Learning