Documents disponibles écrits par cet auteur

Adaptive nonlinear system identification / Ogunfunmi ,Tokunbo

Public ISBD Titre : Adaptive nonlinear system identification : the volterra and wiener model approaches Type de document : document électronique Auteurs : Ogunfunmi ,Tokunbo, Auteur Editeur : Berlin : Springer Année de publication : 2007 Collection : Engineering ISBN/ISSN/EAN : 978-0-387-26328-1 Langues : Anglais (eng) Mots-clés : Traitement  du  signal Théories  non  linéaires Filtres  (mathématiques) Systèmes  adaptatifs  --  Modèles  mathématiques Systèmes  non  linéaires  --  Modèles  mathématiques Systèmes  --  Identification  --  Modèles  mathématiques Index. décimale : 681.51 Systemes de régulation automatique en général.caractéristiques techniques de la cybernétique Résumé : Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches introduces engineers and researchers to the field of nonlinear adaptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-understand methods for identifying nonlinear systems. These methods use adaptive filter algorithms that are well known for linear systems identification. They are applicable for nonlinear systems that can be efficiently modeled by polynomials. After a brief introduction to nonlinear systems and to adaptive system identification, the author presents the discrete Volterra model approach. This is followed by an explanation of the Wiener model approach. Adaptive algorithms using both models are developed. The performance of the two methods are then compared to determine which model performs better for system identification applications. Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches is useful to graduates students, engineers and researchers in the areas of nonlinear systems, control, biomedical systems and in adaptive signal processing. Note de contenu : Table of contents Introduction to Nonlinear Systems.- Polynomial Models for Nonlinear Systems.- Volterra and Wiener Nonlinear Models.- Nonlinear System Indentification Methods.- Introduction to Adaptive Signal Processing.- Nonlinear Adaptive System Identification based on Volterra Models.- Nonlinear Adaptive System Identification based on Wiener Models: Part I.- Nonlinear Adaptive System Identification based on Wiener Models: Part II.- Nonlinear Adaptive System Identification based on Wiener Models: Part III.- Nonlinear Adaptive System Identification based on Wiener Models: Part IV.- Conclusions, Recent Results, and New Directions. Adaptive nonlinear system identification : the volterra and wiener model approaches [document électronique] / Ogunfunmi ,Tokunbo, Auteur . - Springer, 2007. - (Engineering) . ISBN : 978-0-387-26328-1 Langues : Anglais (eng) Mots-clés : Traitement  du  signal Théories  non  linéaires Filtres  (mathématiques) Systèmes  adaptatifs  --  Modèles  mathématiques Systèmes  non  linéaires  --  Modèles  mathématiques Systèmes  --  Identification  --  Modèles  mathématiques Index. décimale : 681.51 Systemes de régulation automatique en général.caractéristiques techniques de la cybernétique Résumé : Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches introduces engineers and researchers to the field of nonlinear adaptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-understand methods for identifying nonlinear systems. These methods use adaptive filter algorithms that are well known for linear systems identification. They are applicable for nonlinear systems that can be efficiently modeled by polynomials. After a brief introduction to nonlinear systems and to adaptive system identification, the author presents the discrete Volterra model approach. This is followed by an explanation of the Wiener model approach. Adaptive algorithms using both models are developed. The performance of the two methods are then compared to determine which model performs better for system identification applications. Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches is useful to graduates students, engineers and researchers in the areas of nonlinear systems, control, biomedical systems and in adaptive signal processing. Note de contenu : Table of contents Introduction to Nonlinear Systems.- Polynomial Models for Nonlinear Systems.- Volterra and Wiener Nonlinear Models.- Nonlinear System Indentification Methods.- Introduction to Adaptive Signal Processing.- Nonlinear Adaptive System Identification based on Volterra Models.- Nonlinear Adaptive System Identification based on Wiener Models: Part I.- Nonlinear Adaptive System Identification based on Wiener Models: Part II.- Nonlinear Adaptive System Identification based on Wiener Models: Part III.- Nonlinear Adaptive System Identification based on Wiener Models: Part IV.- Conclusions, Recent Results, and New Directions.

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	Etat_Exemplaire
E00137	681.51 OGU	Ressources électroniques	Bibliothèque Centrale	Automatique	Disponible
E00138	681.51 OGU	Ressources électroniques	Bibliothèque Centrale	Automatique	Disponible