lauer fabien (11 Ergebnisse)

161 x 245 x 22. xxi, 253 p. Hardcover. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. e Lecture notes in control and information sciences, volume 478. Sprache: Englisch.

Softcover reprint of the original 1st ed. 2019. 16 x 24 cm. XXI, 253 S. XXI, 253 p. 35 illus., 34 illus. in color. Softcover. (Lecture Notes in Control and Information Sciences). Sprache: Englisch.

Hardcover. Zustand: Wie neu. 1. Auflage. As good as new, unread book in excellent condition. Language - English. Ships from Berlin.

Gebundene Ausgabe. Zustand: Sehr gut. Gebraucht - Sehr gut - ungelesen,als Mängelexemplar gekennzeichnet, mit leichten Mängeln an Schnitt oder Umschlag durch Lager- oder Transportschaden -¿Hybrid System Identification helps readers to build mathematical models of dynamical systems switching between different operating modes, from their experimental observations. It provides an overview of the interaction between system identification, machine learning and pattern recognition fields in explaining and analysing hybrid system identification. It emphasises the optimization and computational complexity issues that lie at the core of the problems considered and sets them aside from standard system identification problems. The book presents practical methods that leverage this complexity, as well as a broad view of state-of-the-art machine learning methods.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 253 pp. Englisch.

Zustand: New. In.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Hybrid System Identification | Theory and Algorithms for Learning Switching Models | Fabien Lauer (u. a.) | Taschenbuch | xxi | Englisch | 2019 | Springer | EAN 9783030130916 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Hybrid System Identification helps readers to build mathematical models of dynamical systems switching between different operating modes, from their experimental observations. It provides an overview of the interaction between system identification, machine learning and pattern recognition fields in explaining and analysing hybrid system identification. It emphasises the optimization and computational complexity issues that lie at the core of the problems considered and sets them aside from standard system identification problems. The book presents practical methods that leverage this complexity, as well as a broad view of state-of-the-art machine learning methods.The authors illustrate the key technical points using examples and figures to help the reader understand the material. The book includes an in-depth discussion and computational analysis of hybrid system identification problems, moving from the basic questions of the definition of hybrid systems and system identification to methods of hybrid system identification and the estimation of switched linear/affine and piecewise affine models. The authors also give an overview of the various applications of hybrid systems, discuss the connections to other fields, and describe more advanced material on recursive, state-space and nonlinear hybrid system identification.Hybrid System Identification includes a detailed exposition of major methods, which allows researchers and practitioners to acquaint themselves rapidly with state-of-the-art tools. The book is also a sound basis for graduate and undergraduate students studying this area of control, as the presentation and form of the book provides the background and coverage necessary for a full understanding of hybrid system identification, whether the reader is initially familiar with system identification related to hybrid systems or not.

Paperback. Zustand: Brand New. reprint edition. 276 pages. 9.25x6.10x0.58 inches. In Stock.

Hardcover. Zustand: Brand New. 274 pages. 9.25x6.10x0.79 inches. In Stock.

Zustand: New.