001450609 000__ 03891cam\a2200517\i\4500
001450609 001__ 1450609
001450609 003__ OCoLC
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001450609 020__ $$a9783031097454$$q(electronic bk.)
001450609 020__ $$a3031097459$$q(electronic bk.)
001450609 020__ $$z9783031097447
001450609 020__ $$z3031097440
001450609 0247_ $$a10.1007/978-3-031-09745-4$$2doi
001450609 035__ $$aSP(OCoLC)1348645958
001450609 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dGW5XE$$dOCLCF
001450609 049__ $$aISEA
001450609 050_4 $$aTA1638
001450609 08204 $$a621.36/78$$223/eng/20221025
001450609 24500 $$aCompressed sensing in information processing /$$cGitta Kutyniok, Holger Rauhut, Robert J. Kunsch, editors.
001450609 264_1 $$aCham :$$bBirkhäuser,$$c[2022]
001450609 264_4 $$c©2022
001450609 300__ $$a1 online resource (xvii, 542 pages) :$$billustrations (some color).
001450609 336__ $$atext$$btxt$$2rdacontent
001450609 337__ $$acomputer$$bc$$2rdamedia
001450609 338__ $$aonline resource$$bcr$$2rdacarrier
001450609 4901_ $$aApplied and numerical harmonic analysis
001450609 5050_ $$aHierarchical compressed sensing (G. Wunder) -- Proof Methods for Robust Low-Rank Matrix Recovery (T. Fuchs) -- New Challenges in Covariance Estimation: Multiple Structures and Coarse Quantization (J. Maly) -- Sparse Deterministic and Stochastic Channels: Identification of Spreading Functions and Covariances (Dae Gwan Lee) -- Analysis of Sparse Recovery Algorithms via the Replica Method (A. Bereyhi) -- Unbiasing in Iterative Reconstruction Algorithms for Discrete Compressed Sensing (F.H. Fischer) -- Recovery under Side Constraints (M. Pesavento) -- Compressive Sensing and Neural Networks from a Statistical Learning Perspective (E. Schnoor) -- Angular Scattering Function Estimation Using Deep Neural Networks (Y. Song) -- Fast Radio Propagation Prediction with Deep Learning (R. Levie) -- Active Channel Sparsification: Realizing Frequency Division Duplexing Massive MIMO with Minimal Overhead (M. B. Khalilsarai) -- Atmospheric Radar Imaging Improvements Using Compressed Sensing and MIMO (J. O. Aweda) -- Over-the-Air Computation for Distributed Machine Learning and Consensus in Large Wireless Networks (M. Frey) -- Information Theory and Recovery Algorithms for Data Fusion in Earth Observation (M. Fornasier) -- Sparse Recovery of Sound Fields Using Measurements from Moving Microphones (A. Mertins) -- Compressed Sensing in the Spherical Near-Field to Far-Field Transformation (C. Culotta-Lopez).
001450609 506__ $$aAccess limited to authorized users.
001450609 520__ $$aThis contributed volume showcases the most significant results obtained from the DFG Priority Program on Compressed Sensing in Information Processing. Topics considered revolve around timely aspects of compressed sensing with a special focus on applications, including compressed sensing-like approaches to deep learning; bilinear compressed sensing - efficiency, structure, and robustness; structured compressive sensing via neural network learning; compressed sensing for massive MIMO; and security of future communication and compressive sensing.
001450609 588__ $$aDescription based on print version record.
001450609 650_0 $$aCompressed sensing (Telecommunication)
001450609 655_0 $$aElectronic books.
001450609 7001_ $$aKutyniok, Gitta,$$eeditor.$$1https://isni.org/isni/0000000115939377
001450609 7001_ $$aRauhut, Holger,$$eeditor.$$1https://isni.org/isni/0000000420462093
001450609 7001_ $$aKunsch, Robert J.,$$eeditor.
001450609 77608 $$iPrint version:$$tCompressed sensing in information processing.$$dCham : Springer, 2022$$z9783031097447$$w(OCoLC)1346317750
001450609 830_0 $$aApplied and numerical harmonic analysis.
001450609 852__ $$bebk
001450609 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-09745-4$$zOnline Access$$91397441.1
001450609 909CO $$ooai:library.usi.edu:1450609$$pGLOBAL_SET
001450609 980__ $$aBIB
001450609 980__ $$aEBOOK
001450609 982__ $$aEbook
001450609 983__ $$aOnline
001450609 994__ $$a92$$bISE