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Compressed Sensing

Overview of attention for book
Cover of 'Compressed Sensing & Sparse Filtering'

Table of Contents

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    Book Overview
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    Chapter 1 Compressed Sensing & Sparse Filtering
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    Chapter 2 The Geometry of Compressed Sensing
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    Chapter 3 Sparse Signal Recovery with Exponential-Family Noise
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    Chapter 4 Nuclear Norm Optimization and Its Application to Observation Model Specification
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    Chapter 5 Nonnegative Tensor Decomposition
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    Chapter 6 Sub-Nyquist Sampling and Compressed Sensing in Cognitive Radio Networks
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    Chapter 7 Sparse Nonlinear MIMO Filtering and Identification
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    Chapter 8 Optimization Viewpoint on Kalman Smoothing with Applications to Robust and Sparse Estimation
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    Chapter 9 Compressive System Identification
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    Chapter 10 Distributed Approximation and Tracking Using Selective Gossip
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    Chapter 11 Recursive Reconstruction of Sparse Signal Sequences
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    Chapter 12 Estimation of Time-Varying Sparse Signals in Sensor Networks
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    Chapter 13 Sparsity and Compressed Sensing in Mono-Static and Multi-Static Radar Imaging
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    Chapter 14 Structured Sparse Bayesian Modelling for Audio Restoration
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    Chapter 15 Sparse Representations for Speech Recognition
Attention for Chapter 9: Compressive System Identification
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