Download or read book Nonparametric and Iterative Identification of Nonlinear Systems written by Yun Liu and published by . This book was released on 2006 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonparametric identification of nonlinear dynamic systems written by Kenderi, Gábor and published by KIT Scientific Publishing. This book was released on 2018-11-11 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonparametric System Identification written by Wlodzimierz Greblicki and published by Cambridge University Press. This book was released on 2012-10-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting a thorough overview of the theoretical foundations of non-parametric system identification for nonlinear block-oriented systems, this books shows that non-parametric regression can be successfully applied to system identification, and it highlights the achievements in doing so. With emphasis on Hammerstein, Wiener systems, and their multidimensional extensions, the authors show how to identify nonlinear subsystems and their characteristics when limited information exists. Algorithms using trigonometric, Legendre, Laguerre, and Hermite series are investigated, and the kernel algorithm, its semirecursive versions, and fully recursive modifications are covered. The theories of modern non-parametric regression, approximation, and orthogonal expansions, along with new approaches to system identification (including semiparametric identification), are provided. Detailed information about all tools used is provided in the appendices. This book is for researchers and practitioners in systems theory, signal processing, and communications and will appeal to researchers in fields like mechanics, economics, and biology, where experimental data are used to obtain models of systems.
Download or read book Nonparametric System Identification written by Wlodzimierz Greblicki and published by . This book was released on 2014-05-14 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonparametric Identification of Nonlinear Dynamic Systems written by Gábor Kenderi and published by . This book was released on 2020-10-09 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: A nonparametric identification method for highly nonlinear systems is presented that is able to reconstruct the underlying nonlinearities without a priori knowledge of the describing nonlinear functions. The approach is based on nonlinear Kalman Filter algorithms using the well-known state augmentation technique that turns the filter into a dual state and parameter estimator, of which an extension towards nonparametric identification is proposed in the present work. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Download or read book Parametric and Nonparametric Identification of Nonlinear Systems written by Jin-Song Pei and published by . This book was released on 2001 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Block oriented Nonlinear System Identification written by Fouad Giri and published by Springer Science & Business Media. This book was released on 2010-08-18 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Block-oriented Nonlinear System Identification deals with an area of research that has been very active since the turn of the millennium. The book makes a pedagogical and cohesive presentation of the methods developed in that time. These include: iterative and over-parameterization techniques; stochastic and frequency approaches; support-vector-machine, subspace, and separable-least-squares methods; blind identification method; bounded-error method; and decoupling inputs approach. The identification methods are presented by authors who have either invented them or contributed significantly to their development. All the important issues e.g., input design, persistent excitation, and consistency analysis, are discussed. The practical relevance of block-oriented models is illustrated through biomedical/physiological system modelling. The book will be of major interest to all those who are concerned with nonlinear system identification whatever their activity areas. This is particularly the case for educators in electrical, mechanical, chemical and biomedical engineering and for practising engineers in process, aeronautic, aerospace, robotics and vehicles control. Block-oriented Nonlinear System Identification serves as a reference for active researchers, new comers, industrial and education practitioners and graduate students alike.
Download or read book Nonparametric Identification of Nonlinear Systems written by S. F. Masri and published by . This book was released on 1982 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonlinear System Identification written by Xiao Zhao and published by . This book was released on 1994 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book System Identification for Structured Nonlinear Systems written by Mareike Silke Claassen and published by . This book was released on 2001 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book System Identification written by Lennart Ljung and published by Pearson Education. This book was released on 1998-12-29 with total page 873 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field's leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-fuzzy modeling. The book contains many new computer-based examples designed for Ljung's market-leading software, System Identification Toolbox for MATLAB. Ljung combines careful mathematics, a practical understanding of real-world applications, and extensive exercises. He introduces both black-box and tailor-made models of linear as well as non-linear systems, and he describes principles, properties, and algorithms for a variety of identification techniques: Nonparametric time-domain and frequency-domain methods. Parameter estimation methods in a general prediction error setting. Frequency domain data and frequency domain interpretations. Asymptotic analysis of parameter estimates. Linear regressions, iterative search methods, and other ways to compute estimates. Recursive (adaptive) estimation techniques. Ljung also presents detailed coverage of the key issues that can make or break system identification projects, such as defining objectives, designing experiments, controlling the bias distribution of transfer-function estimates, and carefully validating the resulting models. The first edition of System Identification has been the field's most widely cited reference for over a decade. This new edition will be the new text of choice for anyone concerned with system identification theory and practice.
Download or read book Combined Parametric Nonparametric Identification of Block Oriented Systems written by Grzegorz Mzyk and published by Springer. This book was released on 2013-11-20 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book considers a problem of block-oriented nonlinear dynamic system identification in the presence of random disturbances. This class of systems includes various interconnections of linear dynamic blocks and static nonlinear elements, e.g., Hammerstein system, Wiener system, Wiener-Hammerstein ("sandwich") system and additive NARMAX systems with feedback. Interconnecting signals are not accessible for measurement. The combined parametric-nonparametric algorithms, proposed in the book, can be selected dependently on the prior knowledge of the system and signals. Most of them are based on the decomposition of the complex system identification task into simpler local sub-problems by using non-parametric (kernel or orthogonal) regression estimation. In the parametric stage, the generalized least squares or the instrumental variables technique is commonly applied to cope with correlated excitations. Limit properties of the algorithms have been shown analytically and illustrated in simple experiments.
Download or read book Nonlinear system identification 2 Nonlinear system structure identification written by Robert Haber and published by Springer Science & Business Media. This book was released on 1999 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second part of a two-volume handbook presenting a comprehensive overview of nonlinear dynamic system identification. The books include many aspects of nonlinear processes such as modelling, parameter estimation, structure search, nonlinearity and model validity tests.
Download or read book System Identification for Interconnected Nonlinear Systems written by Kenneth Hsu and published by . This book was released on 2008 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Nonlinear System Identification by Haar Wavelets written by Przemysław Sliwinski and published by Springer Science & Business Media. This book was released on 2012-10-12 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to precisely model real-life systems or man-made devices, both nonlinear and dynamic properties need to be taken into account. The generic, black-box model based on Volterra and Wiener series is capable of representing fairly complicated nonlinear and dynamic interactions, however, the resulting identification algorithms are impractical, mainly due to their computational complexity. One of the alternatives offering fast identification algorithms is the block-oriented approach, in which systems of relatively simple structures are considered. The book provides nonparametric identification algorithms designed for such systems together with the description of their asymptotic and computational properties.
Download or read book Nonlinear System Identification written by Stephen A. Billings and published by John Wiley & Sons. This book was released on 2013-07-29 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 included to 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.
Download or read book Nonlinear Multidegree Dynamic Systems Identification written by S. F. Masri and published by . This book was released on 1980 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
