Compressed Sensing & Sparse Filtering - Couverture souple
Livre 69 sur 180: Signals and Communication Technology
Synopsis
Introduction to Compressed Sensing and Sparse Filtering.- The Geometry of Compressed Sensing.- Sparse Signal Recovery with Exponential-Family Noise.- Nuclear Norm Optimization and its Application to Observation Model Specification.- Nonnegative Tensor Decomposition.- Sub-Nyquist Sampling and Compressed Sensing in Cognitive Radio Networks.- Sparse Nonlinear MIMO Filtering and Identification.- Optimization Viewpoint on Kalman Smoothing with Applications to Robust and Sparse Estimation.- Compressive System Identification.- Distributed Approximation and Tracking using Selective Gossip.- Recursive Reconstruction of Sparse Signal Sequences.- Estimation of Time-Varying Sparse Signals in Sensor Networks.- Sparsity and Compressed Sensing in Mono-static and Multi-static Radar Imaging.- Structured Sparse Bayesian Modelling for Audio Restoration.- Sparse Representations for Speech Recognition.
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