Dewey Class |
515.785 |
Titolo |
Compressed Sensing in Information Processing ( EBook/) / edited by Gitta Kutyniok, Holger Rauhut, Robert J. Kunsch. |
Added Personal Name |
Kutyniok, Gitta |
Rauhut, Holger |
Kunsch, Robert J. |
Other name(s) |
SpringerLink (Online service) |
Edition statement |
1st ed. 2022. |
Pubblicazione |
Cham : : Springer International Publishing : : Imprint: Birkhäuser, , 2022. |
Physical Details |
XVII, 542 p. 116 illus., 90 illus. in color. : online resource. |
Serie |
Applied and numerical harmonic analysis 2296-5017 |
ISBN |
9783031097454 |
Summary Note |
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.: |
Contents note |
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). |
Mode of acces to digital resource |
Digital reproduction.- |
Cham : |
Springer International Publishing, |
2022. - |
Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format. |
System details note |
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users). |
Internet Site |
https://doi.org/10.1007/978-3-031-09745-4 |
Link alle Opere Legate |
Riferimenti soggetto: .
Abstract Harmonic Analysis .
Computational Mathematics and Numerical Analysis .
Digital and Analog Signal Processing .
Harmonic analysis .
Image processing .
Mathematics—Data processing .
Signal processing .
Authors:
Corporate Authors:
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Classification:
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