Nonlinear System Identification by Haar Wavelets
In order to precisely model real-life systems or man-made devices, both nonlinear and dynamic properties need to be taken into account. The generic, black-box model based on Volterra and Wiener series is capable of representing fairly complicated nonlinear and dynamic interactions, however, the resu...
Tallennettuna:
| Päätekijä: | |
|---|---|
| Aineistotyyppi: | Livre numérique |
| Kieli: | Anglais |
| Julkaistu: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Painos: | 1st ed. 2013. |
| Sarja: | Lecture Notes in Statistics
210 |
| Linkit: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Huomautus: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Nonlinear system identification by Haar wavelets, Przemysław Śliwiński, Berlin, Springer, 2013, 1 vol. (XI-139 p.), Lecture notes in statistics, 978-3-642-29395-5 • Nonlinear System Identification by Haar Wavelets, Texte imprimé, 9783642293979 • Nonlinear system identification by Haar wavelets, Przemysław Śliwiński, Berlin, Springer, 2013, 1 vol. (XI-139 p.), Lecture notes in statistics, 978-3-642-29395-5 |
Sisällysluettelo:
- Introduction Hammerstein systems Identification goal Haar orthogonal bases Identification algorithms Computational algorithms. Final remarks. - Technical derivations