A Mathematical Introduction to Compressive Sensing

Holger Rauhut

ISBN 10: 1493900633 / ISBN 13: 9781493900633

Edité par Springer New York, Springer US, 2015

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - At the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domains. In the areas of applied mathematics, electrical engineering, and theoretical computer science, an explosion of research activity has already followed the theoretical results that highlighted the efficiency of the basic principles. The elegant ideas behind these principles are also of independent interest to pure mathematicians.A Mathematical Introduction to Compressive Sensing gives a detailed account of the core theory upon which the field is build. With only moderate prerequisites, it is an excellent textbook for graduate courses in mathematics, engineering, and computer science. It also serves as a reliable resource for practitioners and researchers in these disciplines who want to acquire a careful understanding of the subject. A Mathematical Introduction to Compressive Sensing uses a mathematical perspective to present the core of the theory underlying compressive sensing.

N° de réf. du vendeur 9781493900633

Détails bibliographiques

• Titre: A Mathematical Introduction to Compressive Sensing
• Éditeur: Springer New York, Springer US
• Date de parution: 2015
• Langue: anglais
• ISBN à 10 chiffres: 1493900633
• ISBN à 13 chiffres: 9781493900633
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 235 L x 155 H x 35 P (en millimètres) 235 millimètres de largeur par 155 millimètres de hauteur par 35 millimètres de profondeur
• Poids: 961 grammes

A propos de ce titre

Synopsis

At the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domains. In the areas of applied mathematics, electrical engineering, and theoretical computer science, an explosion of research activity has already followed the theoretical results that highlighted the efficiency of the basic principles. The elegant ideas behind these principles are also of independent interest to pure mathematicians.

A Mathematical Introduction to Compressive Sensing gives a detailed account of the core theory upon which the field is build. With only moderate prerequisites, it is an excellent textbook for graduate courses in mathematics, engineering, and computer science. It also serves as a reliable resource for practitioners and researchers in these disciplines who want to acquire a careful understanding of the subject. A Mathematical Introduction to Compressive Sensing uses a mathematical perspective to present the core of the theory underlying compressive sensing.