Structure Selection and Estimation of Linear Stochastic Dynamic Systems : The Information Criterion Approach PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Structure Selection and Estimation of Linear Stochastic Dynamic Systems : The Information Criterion Approach PDF full book. Access full book title Structure Selection and Estimation of Linear Stochastic Dynamic Systems : The Information Criterion Approach by VERES SÁNDOR.. Download full books in PDF and EPUB format.
Author: VERES SÁNDOR.
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Author: VERES SÁNDOR.
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Author: Sandor M. Veres
Publisher: CRC Press
ISBN: 9782881247156
Category : Mathematics
Languages : en
Pages : 362
Get Book Here
Book Description
This book gives a reliable review on structure selection of stochastic dynamic systems using information criteria AIC, BIC, o and stochastic complexity. After theoretical investigations many simulations are estimators, which illustrate both the effectiveness and the limitations of these methods. The reader can gain his or her own experience on the"working" of many methods (associated with different parameter estimators) using the demonstration disk which can be run on most IBM-compatible personal computers. The book will be helpful to anybody interested in applying automated methods of model-structure selection inn control engineering, in time series analysis or in signal processing.
Author: Sandor M. Veres
Publisher: CRC Press
ISBN: 9782881247156
Category : Mathematics
Languages : en
Pages : 356
Get Book Here
Book Description
This book gives a reliable review on structure selection of stochastic dynamic systems using information criteria AIC, BIC, o and stochastic complexity. After theoretical investigations many simulations are estimators, which illustrate both the effectiveness and the limitations of these methods. The reader can gain his or her own experience on the"working" of many methods (associated with different parameter estimators) using the demonstration disk which can be run on most IBM-compatible personal computers. The book will be helpful to anybody interested in applying automated methods of model-structure selection inn control engineering, in time series analysis or in signal processing.
Author: Sándor M. Veres
Publisher:
ISBN:
Category :
Languages : en
Pages : 342
Get Book Here
Book Description
Author: Jan C. Willems
Publisher: Springer Science & Business Media
ISBN: 3642750079
Category : Business & Economics
Languages : en
Pages : 254
Get Book Here
Book Description
The problem of obtaining dynamical models directly from an observed time-series occurs in many fields of application. There are a number of possible approaches to this problem. In this volume a number of such points of view are exposed: the statistical time series approach, a theory of guaranted performance, and finally a deterministic approximation approach. This volume is an out-growth of a number of get-togethers sponsered by the Systems and Decision Sciences group of the International Institute of Applied Systems Analysis (IIASA) in Laxenburg, Austria. The hospitality and support of this organization is gratefully acknowledged. Jan Willems Groningen, the Netherlands May 1989 TABLE OF CONTENTS Linear System Identification- A Survey page 1 M. Deistler A Tutorial on Hankel-Norm Approximation 26 K. Glover A Deterministic Approach to Approximate Modelling 49 C. Heij and J. C. Willems Identification - a Theory of Guaranteed Estimates 135 A. B. Kurzhanski Statistical Aspects of Model Selection 215 R. Shibata Index 241 Addresses of Authors 246 LINEAR SYSTEM IDENTIFICATION· A SURVEY M. DEISTLER Abstract In this paper we give an introductory survey on the theory of identification of (in general MIMO) linear systems from (discrete) time series data. The main parts are: Structure theory for linear systems, asymptotic properties of maximum likelihood type estimators, estimation of the dynamic specification by methods based on information criteria and finally, extensions and alternative approaches such as identification of unstable systems and errors-in-variables. Keywords Linear systems, parametrization, maximum likelihood estimation, information criteria, errors-in-variables.
Author: Anders Lindquist
Publisher: Springer
ISBN: 3662457504
Category : Science
Languages : en
Pages : 788
Get Book Here
Book Description
This book presents a treatise on the theory and modeling of second-order stationary processes, including an exposition on selected application areas that are important in the engineering and applied sciences. The foundational issues regarding stationary processes dealt with in the beginning of the book have a long history, starting in the 1940s with the work of Kolmogorov, Wiener, Cramér and his students, in particular Wold, and have since been refined and complemented by many others. Problems concerning the filtering and modeling of stationary random signals and systems have also been addressed and studied, fostered by the advent of modern digital computers, since the fundamental work of R.E. Kalman in the early 1960s. The book offers a unified and logically consistent view of the subject based on simple ideas from Hilbert space geometry and coordinate-free thinking. In this framework, the concepts of stochastic state space and state space modeling, based on the notion of the conditional independence of past and future flows of the relevant signals, are revealed to be fundamentally unifying ideas. The book, based on over 30 years of original research, represents a valuable contribution that will inform the fields of stochastic modeling, estimation, system identification, and time series analysis for decades to come. It also provides the mathematical tools needed to grasp and analyze the structures of algorithms in stochastic systems theory.
Author: Torsten Söderström
Publisher: Springer Science & Business Media
ISBN: 1447101014
Category : Mathematics
Languages : en
Pages : 387
Get Book Here
Book Description
This comprehensive introduction to the estimation and control of dynamic stochastic systems provides complete derivations of key results. The second edition includes improved and updated material, and a new presentation of polynomial control and new derivation of linear-quadratic-Gaussian control.
Author: Manolis Papadrakakis
Publisher: Springer Science & Business Media
ISBN: 9400751346
Category : Technology & Engineering
Languages : en
Pages : 362
Get Book Here
Book Description
The considerable influence of inherent uncertainties on structural behavior has led the engineering community to recognize the importance of a stochastic approach to structural problems. Issues related to uncertainty quantification and its influence on the reliability of the computational models are continuously gaining in significance. In particular, the problems of dynamic response analysis and reliability assessment of structures with uncertain system and excitation parameters have been the subject of continuous research over the last two decades as a result of the increasing availability of powerful computing resources and technology. This book is a follow up of a previous book with the same subject (ISBN 978-90-481-9986-0) and focuses on advanced computational methods and software tools which can highly assist in tackling complex problems in stochastic dynamic/seismic analysis and design of structures. The selected chapters are authored by some of the most active scholars in their respective areas and represent some of the most recent developments in this field. The book consists of 21 chapters which can be grouped into several thematic topics including dynamic analysis of stochastic systems, reliability-based design, structural control and health monitoring, model updating, system identification, wave propagation in random media, seismic fragility analysis and damage assessment. This edited book is primarily intended for researchers and post-graduate students who are familiar with the fundamentals and wish to study or to advance the state of the art on a particular topic in the field of computational stochastic structural dynamics. Nevertheless, practicing engineers could benefit as well from it as most code provisions tend to incorporate probabilistic concepts in the analysis and design of structures.
Author: P. R. Kumar
Publisher: SIAM
ISBN: 1611974267
Category : Mathematics
Languages : en
Pages : 371
Get Book Here
Book Description
Since its origins in the 1940s, the subject of decision making under uncertainty has grown into a diversified area with application in several branches of engineering and in those areas of the social sciences concerned with policy analysis and prescription. These approaches required a computing capacity too expensive for the time, until the ability to collect and process huge quantities of data engendered an explosion of work in the area. This book provides succinct and rigorous treatment of the foundations of stochastic control; a unified approach to filtering, estimation, prediction, and stochastic and adaptive control; and the conceptual framework necessary to understand current trends in stochastic control, data mining, machine learning, and robotics.?
Author: Rolf Isermann
Publisher: Springer
ISBN: 9783540871552
Category : Technology & Engineering
Languages : en
Pages : 705
Get Book Here
Book Description
Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.
