Extracting knowledge from time series : an introduction to nonlinear empirical modeling
This book addresses the fundamental question of how to construct mathematical models for the evolution of dynamical systems from experimentally-obtained time series. It places emphasis on chaotic signals and nonlinear modeling and discusses different approaches to the forecast of future system evolu...
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| Auteurs principaux: | , |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Édition: | 1st ed. 2010. |
| Collection: | Springer Series in Synergetics
|
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Extracting knowledge from time series, an introduction to nonlinear empirical modeling, Boris P. Bezruchko, Dmitry A. Smirnov, 2010, Heidelberg, Springer, 1 vol. (xxi, 405 pages), Springer complexity, 978-3-642-12600-0 • Extracting knowledge from time series, an introduction to nonlinear empirical modeling, Boris P. Bezruchko, Dmitry A. Smirnov, 2010, Heidelberg, Springer, 1 vol. (xxi, 405 pages), Springer complexity, 978-3-642-12600-0 • Extracting Knowledge From Time Series, Texte imprimé, 9783642264825 • Extracting Knowledge From Time Series, Texte imprimé, 9783642126024 |