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Identification, Adaptation, Learning: The Science of Learning Models from Data: NATO ASI Subseries F:, cartea 153

Editat de Sergio Bittanti, Giorgio Picci
en Limba Engleză Hardback – iul 1996
This book collects the lectures given at the NATO Advanced Study Institute From Identijication to Learning held in Villa Olmo, Como, Italy, from August 22 to September 2, 1994. The school was devoted to the themes of Identijication, Adaptation and Learning, as they are currently understood in the Information and Contral engineering community, their development in the last few decades, their inter­ connections and their applications. These titles describe challenging, exciting and rapidly growing research areas which are of interest both to contral and communication engineers and to statisticians and computer scientists. In accordance with the general goals of the Institute, and notwithstanding the rat her advanced level of the topics discussed, the presentations have been generally kept at a fairly tutorial level. For this reason this book should be valuable to a variety of rearchers and to graduate students interested in the general area of Control, Signals and Information Pracessing. As the goal of the school was to explore a common methodologicalline of reading the issues, the flavor is quite interdisciplinary. We regard this as an original and valuable feature of this book.
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Specificații

ISBN-13: 9783540610809
ISBN-10: 3540610804
Pagini: 588
Ilustrații: XXI, 552 p.
Dimensiuni: 155 x 235 x 37 mm
Greutate: 1.03 kg
Ediția:1996
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria NATO ASI Subseries F:

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Geometric Methods for State Space Identification.- Parameter Estimation of Multivariable Systems Using Balanced Realizations.- Balanced Canonical Forms.- From Data to State Model.- Identification of Linear Systems from Noisy Data.- Identification in H?: Theory and Applications.- System Identification with Information Theoretic Criteria.- Least Squares Based Self-Tuning Control Systems.- On Neural Network Model Structures in System Identification.- An Overview of Computational Learning Theory and Its Applications to Neural Network Training.- Just-in-Time Learning and Estimation.- Wavelets in Identification.- Fuzzy Logic Modelling and Control.- Searching for the Best: Stochastic Approximation, Simulated Annealing and Related Procedures.- List of Contributors.