Format:
1 Online-Ressource(XVII, 542 p. 116 illus., 90 illus. in color.)
Edition:
1st ed. 2022.
ISBN:
9783031097454
Series Statement:
Applied and Numerical Harmonic Analysis
Content:
Hierarchical compressed sensing (G. Wunder) -- Proof Methods for Robust Low-Rank Matrix Recovery (T. Fuchs) -- New Challenges in Covariance Estimation: Multiple Structures and Coarse Quantization (J. Maly) -- Sparse Deterministic and Stochastic Channels: Identification of Spreading Functions and Covariances (Dae Gwan Lee) -- Analysis of Sparse Recovery Algorithms via the Replica Method (A. Bereyhi) -- Unbiasing in Iterative Reconstruction Algorithms for Discrete Compressed Sensing (F.H. Fischer) -- Recovery under Side Constraints (M. Pesavento) -- Compressive Sensing and Neural Networks from a Statistical Learning Perspective (E. Schnoor) -- Angular Scattering Function Estimation Using Deep Neural Networks (Y. Song) -- Fast Radio Propagation Prediction with Deep Learning (R. Levie) -- Active Channel Sparsification: Realizing Frequency Division Duplexing Massive MIMO with Minimal Overhead (M. B. Khalilsarai) -- Atmospheric Radar Imaging Improvements Using Compressed Sensing and MIMO (J. O. Aweda) -- Over-the-Air Computation for Distributed Machine Learning and Consensus in Large Wireless Networks (M. Frey) -- Information Theory and Recovery Algorithms for Data Fusion in Earth Observation (M. Fornasier) -- Sparse Recovery of Sound Fields Using Measurements from Moving Microphones (A. Mertins) -- Compressed Sensing in the Spherical Near-Field to Far-Field Transformation (C. Culotta-López).
Content:
This contributed volume showcases the most significant results obtained from the DFG Priority Program on Compressed Sensing in Information Processing. Topics considered revolve around timely aspects of compressed sensing with a special focus on applications, including compressed sensing-like approaches to deep learning; bilinear compressed sensing - efficiency, structure, and robustness; structured compressive sensing via neural network learning; compressed sensing for massive MIMO; and security of future communication and compressive sensing.
Additional Edition:
ISBN 9783031097447
Additional Edition:
ISBN 9783031097461
Additional Edition:
ISBN 9783031097478
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031097447
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031097461
Additional Edition:
Erscheint auch als Druck-Ausgabe ISBN 9783031097478
Additional Edition:
Erscheint auch als Druck-Ausgabe Compressed sensing in information processing Cham, Switzerland : Birkhäuser, 2022 ISBN 9783031097447
Language:
English
DOI:
10.1007/978-3-031-09745-4
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