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Lieferstatus:	i.d.R. innert 14-24 Tagen versandfertig
Veröffentlichung:	Juli 2010
Genre:	Schulbücher
	Angewandte Mathematik / Bildverarbeitung / Differenzialgleichung / Differenzialrechnung / Enzyklopädie / Foto- und Bildbearbeitung / Gleichung / Differenzialgleichung / Grafik (EDV) / Bildverarbeitung / MATHEMATICS / Applied / MATHEMATICS / Differential Equations / General / Mathematik / Mathematik / Statistik / Nachschlagewerke / Numerik (naturwissenschaftlich, EDV) / Numerische Mathematik / Signal (techn.) / Stochastik / Wahrscheinlichkeitsrechnung / Wahrscheinlichkeitsrechnung und Statistik
ISBN:	9783110226140
EAN-Code:	9783110226140
Verlag:	De Gruyter
Einband:	Gebunden
Sprache:	English
Serie:	#9 - Radon Series on Computational and Applied Mathematics
Dimensionen:	H 246 mm / B 175 mm / D 24 mm
Gewicht:	776 gr
Seiten:	352
Zus. Info:	HC runder Rücken kaschiert
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

The present collection is the very first contribution of this type in the field of sparse recovery. Compressed sensing is one of the important facets of the broader concept presented in the book, which by now has made connections with other branches such as mathematical imaging, inverse problems, numerical analysis and simulation. The book consists of four lecture notes of courses given at the Summer School on "Theoretical Foundations and Numerical Methods for Sparse Recovery" held at the Johann Radon Institute for Computational and Applied Mathematics in Linz, Austria, in September 2009. This unique collection will be of value for a broad community and may serve as a textbook for graduate courses. From the contents: "Compressive Sensing and Structured Random Matrices" by Holger Rauhut "Numerical Methods for Sparse Recovery" by Massimo Fornasier "Sparse Recovery in Inverse Problems" by Ronny Ramlau and Gerd Teschke "An Introduction to Total Variation for Image Analysis" by Antonin Chambolle, Vicent Caselles, Daniel Cremers, Matteo Novaga and Thomas Pock