Chapter 1 A Survey of Compressed Sensing

Chapter 2 Temporal Compressive Sensing for Video

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 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