Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal DomainsJohn Wiley & Sons, 2013 M07 29 - 576 páginas Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of:
NARMAX algorithms provide a fundamentally different approach to nonlinear system identification and signal processing for nonlinear systems. NARMAX methods provide models that are transparent, which can easily be analysed, and which can be used to solve real problems. This book is intended for graduates, postgraduates and researchers in the sciences and engineering, and also for users from other fields who have collected data and who wish to identify models to help to understand the dynamics of their systems. |
Contenido
Feature Selection and Rankin | |
Model Validation | |
The Identification and Analysis of Nonlinear Systems | |
Design of Nonlinear Systems in the Frequency Domain | |
Neural Networks for Nonlinear System Identification | |
Chaos | |
Identification of ContinuousTime Nonlinear Models | |
differential Equation Models Without Differentiation | |
TimeVarying and Nonlinear System Identification | |
Identification of Cellular Automata and NState Models | |
Identification of Coupled Map Lattice and Partial | |
Case Studies | |
Index | |
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Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and ... Stephen A. Billings Vista previa limitada - 2013 |