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An Introduction to Sparse Stochastic Processes

  • Livre Relié
  • 384 Nombre de pages
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Informationen zum Autor Michael Unser is Professor and Director of EPFL's Biomedical Imaging Group, Switzerland. He is a member of... Lire la suite
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Description

Informationen zum Autor Michael Unser is Professor and Director of EPFL's Biomedical Imaging Group, Switzerland. He is a member of the Swiss Academy of Engineering Sciences, a Fellow of EURASIP, and a Fellow of the IEEE. Pouya D. Tafti is researcher at Qlaym GmbH, Dusseldorf, and a former member of the Biomedical Imaging Group at EPFL, where he conducted research on the theory and applications of probabilistic models for data. Klappentext A detailed guide to sparse processes, providing a description of their transform-domain statistics and applying the models to practical algorithms. Zusammenfassung Providing a novel approach to sparsity, this comprehensive book presents the theory of stochastic processes that are ruled by linear stochastic differential equations, and sets out a general stochastic framework for developing efficient and practical nonlinear algorithms. Inhaltsverzeichnis 1. Introduction; 2. Roadmap to the book; 3. Mathematical context and background; 4. Continuous-domain innovation models; 5. Operators and their inverses; 6. Splines and wavelets; 7. Sparse stochastic processes; 8. Sparse representations; 9. Infinite divisibility and transform-domain statistics; 10. Recovery of sparse signals; 11. Wavelet-domain methods; 12. Conclusion; Appendix A. Singular integrals; Appendix B. Positive definiteness; Appendix C. Special functions.

Texte du rabat

A detailed guide to sparse processes, providing a description of their transform-domain statistics and applying the models to practical algorithms.



Résumé
Providing a novel approach to sparsity, this comprehensive book presents the theory of stochastic processes that are ruled by linear stochastic differential equations, and sets out a general stochastic framework for developing efficient and practical nonlinear algorithms.

Contenu

1. Introduction; 2. Roadmap to the book; 3. Mathematical context and background; 4. Continuous-domain innovation models; 5. Operators and their inverses; 6. Splines and wavelets; 7. Sparse stochastic processes; 8. Sparse representations; 9. Infinite divisibility and transform-domain statistics; 10. Recovery of sparse signals; 11. Wavelet-domain methods; 12. Conclusion; Appendix A. Singular integrals; Appendix B. Positive definiteness; Appendix C. Special functions.

Informations sur le produit

Titre: An Introduction to Sparse Stochastic Processes
Auteur:
Code EAN: 9781107058545
ISBN: 978-1-107-05854-5
Format: Livre Relié
Editeur: Cambridge University Press
Genre: Electrotechnique
nombre de pages: 384
Poids: 924g
Taille: H259mm x B172mm x T23mm
Année: 2014

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