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Bücher Englische Bücher Wissen & Bildung Naturwissenschaft, Medizin, Informatik, Technik Physik & Astronomie Elektrizität, Magnetismus, Optik Nonlinear System Identification
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Nonlinear System Identification
Oliver Nelles (Gebundene Ausgabe, Englisch)
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Beschreibung
This book provides engineers and scientists in academia and industry with a thorough understanding of the underlying principles of nonlinear system identification. It equips them to apply the models and methods discussed to real problems with confidence, while also making them aware of potential difficulties that may arise in practice.
Moreover, the book is self-contained, requiring only a basic… grasp of matrix algebra, signals and systems, and statistics. Accordingly, it can also serve as an introduction to linear system identification, and provides a practical overview of the major optimization methods used in engineering. The focus is on gaining an intuitive understanding of the subject and the practical application of the techniques discussed. The book is not written in a theorem/proof style; instead, the mathematics is kept to a minimum, and the ideas covered are illustrated with numerous figures, examples, and real-world applications.
In the past, nonlinear system identification was a field characterized by a variety of ad-hoc approaches, each applicable only to a very limited class of systems. With the advent of neural networks, fuzzy models, Gaussian process models, and modern structure optimization techniques, a much broader class of systems can now be handled. Although one major aspect of nonlinear systems is that virtually every one is unique, tools have since been developed that allow each approach to be applied to a wide variety of systems. Dieses Produkt haben wir gerade leider nicht auf Lager.
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Technische Daten
Erscheinungsdatum
30.09.2022
Sprache
Englisch
EAN
9783030474386
Herausgeber
Springer International Publishing
Sonderedition
Nein
Autor
Oliver Nelles
Seitenanzahl
1225
Auflage
2nd edition 2020
Einbandart
Gebundene Ausgabe
Buch Untertitel
From Classical Approaches to Neural Networks, Fuzzy Models, and Gaussian Processes
Schlagwörter
Fuzzy and neuro-fuzzy models, Linear optimization, Nonlinear local optimization, Linear and nonlinear dynamic system identification, Identification of dynamic systems, Local model networks HILOMOT, Nonlinear finite impulse response (NFIR), Long short-term memory (LSTM) networks, complexity
Thema-Inhalt
PHJ - Optische Physik
TJFM - Regelungstechnik
TBJ - Mathematik für Ingenieure
GPFC - Kybernetik und Systemtheorie
PBU - Optimierung
UYM - Computermodellierung und -simulation
Höhe
235 mm
Breite
15.5 cm
Hersteller: Springer Nature Customer Service Center GmbH, Europaplatz 3, Heidelberg, Deutschland, 69115, ProductSafety@springernature.com
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