Low Rank Approximation : Algorithms, Implementation, Applications
Matrix low-rank approximation is intimately related to data modelling; a problem that arises frequently in many different fields. Low Rank Approximation: Algorithms, Implementation, Applications is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approxim...
Guardat en:
| Autor principal: | |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
London :
Springer London : Imprint: Springer
[20..].
Cham : Springer Nature |
| Edició: | 1st ed. 2012. |
| Col·lecció: | Communications and Control Engineering
|
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Low rank approximation, algorithms, implementation, applications, Ivan Markovsky, London, Springer, 2012, 1 volume (x-256 pages), Communications and control engineering, 978-1-447-12226-5 |
Taula de continguts:
- Introduction From Data to Models Applications in System and Control Theory Applications in Signal Processing Applications in Computer Algebra Applications in Machine Learing Subspace-type Algorithms Algorithms Based on Local Optimization Data Smoothing and Filtering Recursive Algorithms