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Author: Bernard Friedland Publisher: Courier Corporation ISBN: 048613511X Category : Science Languages : en Pages : 530
Book Description
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: Bernard Friedland Publisher: Courier Corporation ISBN: 048613511X Category : Science Languages : en Pages : 530
Book Description
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 ISBN: 0471735558 Category : Technology & Engineering Languages : en Pages : 485
Book Description
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: James Durbin Publisher: OUP Oxford ISBN: 0191627194 Category : Business & Economics Languages : en Pages : 369
Book Description
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: Tom Hollenstein Publisher: Springer Science & Business Media ISBN: 1461450071 Category : Psychology Languages : en Pages : 135
Book Description
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: Junichiro Hagiwara Publisher: Springer Nature ISBN: 9811607117 Category : Mathematics Languages : en Pages : 350
Book Description
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: Chang-Jin Kim Publisher: Mit Press ISBN: 9780262112383 Category : Business & Economics Languages : en Pages : 297
Book Description
Both state-space models and Markov switching models have been highly productive paths for empirical research in macroeconomics and finance. This book presents recent advances in econometric methods that make feasible the estimation of models that have both features. One approach, in the classical framework, approximates the likelihood function; the other, in the Bayesian framework, uses Gibbs-sampling to simulate posterior distributions from data.The authors present numerous applications of these approaches in detail: decomposition of time series into trend and cycle, a new index of coincident economic indicators, approaches to modeling monetary policy uncertainty, Friedman's "plucking" model of recessions, the detection of turning points in the business cycle and the question of whether booms and recessions are duration-dependent, state-space models with heteroskedastic disturbances, fads and crashes in financial markets, long-run real exchange rates, and mean reversion in asset returns.
Author: John S. Bay Publisher: McGraw-Hill Science, Engineering & Mathematics ISBN: Category : Mathematics Languages : en Pages : 600
Book Description
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 ISBN: 0470754710 Category : Social Science Languages : en Pages : 368
Book Description
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: Masanao Aoki Publisher: Springer Science & Business Media ISBN: 3642969852 Category : Business & Economics Languages : en Pages : 324
Book Description
model's predictive capability? These are some of the questions that need to be answered in proposing any time series model construction method. This book addresses these questions in Part II. Briefly, the covariance matrices between past data and future realizations of time series are used to build a matrix called the Hankel matrix. Information needed for constructing models is extracted from the Hankel matrix. For example, its numerically determined rank will be the di mension of the state model. Thus the model dimension is determined by the data, after balancing several sources of error for such model construction. The covariance matrix of the model forecasting error vector is determined by solving a certain matrix Riccati equation. This matrix is also the covariance matrix of the innovation process which drives the model in generating model forecasts. In these model construction steps, a particular model representation, here referred to as balanced, is used extensively. This mode of model representation facilitates error analysis, such as assessing the error of using a lower dimensional model than that indicated by the rank of the Hankel matrix. The well-known Akaike's canonical correlation method for model construc tion is similar to the one used in this book. There are some important differ ences, however. Akaike uses the normalized Hankel matrix to extract canonical vectors, while the method used in this book does not normalize the Hankel ma trix.
Author: Bernard Friedland
Author: Bernard Friedland
Author: Robert L. Williams, II
Author: James Durbin
Author: Tom Hollenstein
Author: Junichiro Hagiwara
Author: Chang-Jin Kim
Author: John S. Bay
Author: E. Walter
Author: Neil Brenner
Author: Masanao Aoki