State Space
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Author | : Bernard Friedland |
Publisher | : Courier Corporation |
Total Pages | : 530 |
Release | : 2012-03-08 |
Genre | : Science |
ISBN | : 048613511X |
Introduction to state-space methods covers feedback control; state-space representation of dynamic systems and dynamics of linear systems; frequency-domain analysis; controllability and observability; shaping the dynamic response; more. 1986 edition.
Author | : Robert L. Williams, II |
Publisher | : John Wiley & Sons |
Total Pages | : 485 |
Release | : 2007-02-09 |
Genre | : Technology & Engineering |
ISBN | : 0471735558 |
The book blends readability and accessibility common to undergraduate control systems texts with the mathematical rigor necessary to form a solid theoretical foundation. Appendices cover linear algebra and provide a Matlab overivew and files. The reviewers pointed out that this is an ambitious project but one that will pay off because of the lack of good up-to-date textbooks in the area.
Author | : Tom Hollenstein |
Publisher | : Springer Science & Business Media |
Total Pages | : 135 |
Release | : 2012-10-28 |
Genre | : Psychology |
ISBN | : 1461450071 |
Human development from birth through adulthood is a complex interplay of many interacting forces. Children’s internal processes are manifest in behaviors that are sculpted by their experiences, most notably with primary caregivers. Because the discipline of psychology explores human behavior and cognition, the techniques employed for developmental analysis must be able to describe, depict, and quantify these complex processes. State Space Grids provides the framework, basic method, rationale, and advanced techniques for translating the behavior of children, adolescents, and parents into visible, traceable data. This seminar-between-covers takes readers step by step from conceptualization through implementation of projects, with examples from a range of current research within and outside child development. Links are included for the GridWare software program and related user resources. And although state space grids need not be used only to analyze dynamic systems, they serve as an excellent tool for honing systemic thinking. Key coverage in this volume includes: Dynamic systems and the origins of state space grids. The state of research using state space grids. Introducing GridWare and how it works. How to use state space grids, from idea through finished project. Within-grid and between-grid analysis. Conducting advanced analysis. State Space Grids is an essential reference for researchers across such disciplines as psychology, neuroscience, economics, computer science, and agricultural science.
Author | : John S. Bay |
Publisher | : McGraw-Hill Science, Engineering & Mathematics |
Total Pages | : 600 |
Release | : 1999 |
Genre | : Mathematics |
ISBN | : |
Spans a broad range of linear system theory concepts, but does so in a complete and sequential style. It is suitable for a first-year graduate or advanced undergraduate course in any field of engineering. State space methods are derived from first principles while drawing on the students' previous understanding of physical and mathematical concepts. The text requires only a knowledge of basic signals and systems theory, but takes the student, in a single semester, all the way through state feedback, observers, Kalman filters, and elementary I.Q.G. control.
Author | : Neil Brenner |
Publisher | : John Wiley & Sons |
Total Pages | : 368 |
Release | : 2008-04-15 |
Genre | : Social Science |
ISBN | : 0470754710 |
This groundbreaking, interdisciplinary volume brings together diverse analyses of state space in historical and contemporary capitalism. The first volume to present an accessible yet challenging overview of the changing geographies of state power under capitalism. A unique, interdisciplinary collection of contributions by major theorists and analysts of state spatial restructuring in the current era. Investigates some of the new political spaces that are emerging under contemporary conditions of ‘globalization'. Explores state restructuring on multiple spatial scales, and from a range of theoretical, methodological and empirical perspectives. Covers a range of topical issues in contemporary geographical political economy. Contains case study material on Western Europe, North America and East Asia, as well as parts of Africa and South America.
Author | : E. Walter |
Publisher | : Springer Science & Business Media |
Total Pages | : 210 |
Release | : 2013-03-07 |
Genre | : Mathematics |
ISBN | : 3642618235 |
Author | : Kostas Triantafyllopoulos |
Publisher | : Springer Nature |
Total Pages | : 503 |
Release | : 2021-11-12 |
Genre | : Mathematics |
ISBN | : 303076124X |
Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.
Author | : James Durbin |
Publisher | : OUP Oxford |
Total Pages | : 369 |
Release | : 2012-05-03 |
Genre | : Business & Economics |
ISBN | : 0191627194 |
This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series. Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations. Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.
Author | : Junichiro Hagiwara |
Publisher | : Springer Nature |
Total Pages | : 350 |
Release | : 2021-08-30 |
Genre | : Mathematics |
ISBN | : 9811607117 |
This book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent Bayesian treatment regarding whole combinations of batch and sequential solutions for linear Gaussian and general state-space models: MCMC and Kalman/particle filter. The reader is given insight on flexible modeling in modern time series analysis. The main topics of the book deal with the state-space model, covering extensively, from introductory and exploratory methods to the latest advanced topics such as real-time structural change detection. Additionally, a practical exercise using R/Stan based on real data promotes understanding and enhances the reader’s analytical capability.
Author | : David F. Delchamps |
Publisher | : Springer Science & Business Media |
Total Pages | : 431 |
Release | : 2012-12-06 |
Genre | : Science |
ISBN | : 1461238161 |
It is difficult for me to forget the mild sense of betrayal I felt some ten years ago when I discovered, with considerable dismay, that my two favorite books on linear system theory - Desoer's Notes for a Second Course on Linear Systems and Brockett's Finite Dimensional Linear Systems - were both out of print. Since that time, of course, linear system theory has undergone a transformation of the sort which always attends the maturation of a theory whose range of applicability is expanding in a fashion governed by technological developments and by the rate at which such advances become a part of engineering practice. The growth of the field has inspired the publication of some excellent books; the encyclopedic treatises by Kailath and Chen, in particular, come immediately to mind. Nonetheless, I was inspired to write this book primarily by my practical needs as a teacher and researcher in the field. For the past five years, I have taught a one semester first year gradu ate level linear system theory course in the School of Electrical Engineering at Cornell. The members of the class have always come from a variety of departments and backgrounds, and con sequently have entered the class with levels of preparation ranging from first year calculus and a taste of transform theory on the one extreme to senior level real analysis and abstract algebra on the other.