Identification, Adaptation, Learning: The Science of Learning Models from Data: 153 - Brossura

 
9783642082481: Identification, Adaptation, Learning: The Science of Learning Models from Data: 153

Sinossi

This book offers a tutorial view of the science of learning models from data. It covers the most important approaches to linear modelling, nonlinear model construction from data, fuzzy logic based modelling, and optimization methods.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Contenuti

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.