Isbn: 9781119943594 - nonlinear system identification: narmax methods in the time, frequency, and spatio-temporal domains (11 resultados)

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New. Stephen A. Billings is Professor of Signal Processing and Complex Systems, and Director of the Signal Processing and Complex Systems Research Group, in the Department of Automatic Control and Systems Engineering at the University of Sheffield, He is counted.

Hardcover. Condición: Brand New. 1st edition. 574 pages. 9.61x6.61x1.00 inches. In Stock.

Buch. Condición: Neu. Neuware - 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: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) model The orthogonal least squares algorithm that allows models to be built term by term where the error reduction ratio reveals the percentage contribution of each model term Statistical and qualitative model validation methods that can be applied to any model class Generalised frequency response functions which provide significant insight into nonlinear behaviours A completely new class of filters that can move, split, spread, and focus energy The response spectrum map and the study of sub harmonic and severely nonlinear systems Algorithms that can track rapid time variation in both linear and nonlinear systems The important class of spatio-temporal systems that evolve over both space and time Many case study examples from modelling space weather, through identification of a model of the visual processing system of fruit flies, to tracking causality in EEG data are all includedto demonstrate how easily the methods can be applied in practice and to show the insight that the algorithms reveal even for complex systems 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.…

Hardcover. Condición: new. Hardcover. 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: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) modelThe orthogonal least squares algorithm that allows models to be built term by term where the error reduction ratio reveals the percentage contribution of each model termStatistical and qualitative model validation methods that can be applied to any model classGeneralised frequency response functions which provide significant insight into nonlinear behavioursA completely new class of filters that can move, split, spread, and focus energyThe response spectrum map and the study of sub harmonic and severely nonlinear systemsAlgorithms that can track rapid time variation in both linear and nonlinear systemsThe important class of spatio-temporal systems that evolve over both space and timeMany case study examples from modelling space weather, through identification of a model of the visual processing system of fruit flies, to tracking causality in EEG data are all includedto demonstrate how easily the methods can be applied in practice and to show the insight that the algorithms reveal even for complex systems 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. This book helps practitioners and researchers find ways to solve difficult nonlinear system identification problems using the well-established NARMAX method. It is a description of a class of system identification algorithms that can be used to identify nonlinear dynamic models from recorded data. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condición: New. Print on Demand pp. 574.

Condición: New. PRINT ON DEMAND pp. 574.