Discrete Time Dynamic Models
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| Author | : Ronald K. Pearson |
| Publisher | : Oxford University Press |
| Total Pages | : 481 |
| Release | : 1999-12-02 |
| Genre | : Mathematics |
| ISBN | : 0195352815 |
Fueled by advances in computer technology, model-based approaches to the control of industrial processes are now widespread. While there is an enormous literature on modeling, the difficult first step of selecting an appropriate model structure has received almost no attention. This book fills the gap, providing practical insight into model selection for chemical processes and emphasizing structures suitable for control system design.
| Author | : Ulrich Krause |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 366 |
| Release | : 2015-03-10 |
| Genre | : Mathematics |
| ISBN | : 3110365693 |
This book provides a systematic, rigorous and self-contained treatment of positive dynamical systems. A dynamical system is positive when all relevant variables of a system are nonnegative in a natural way. This is in biology, demography or economics, where the levels of populations or prices of goods are positive. The principle also finds application in electrical engineering, physics and computer sciences. "The author has greatly expanded the field of positive systems in surprising ways." - Prof. Dr. David G. Luenberger, Stanford University(USA)
| Author | : Brian Ferguson |
| Publisher | : Routledge |
| Total Pages | : 347 |
| Release | : 2003-07-10 |
| Genre | : Business & Economics |
| ISBN | : 1134440545 |
This new book will be welcomed by econometricians and students of econometrics everywhere. Introducing discrete time modelling techniques and bridging the gap between economics and econometric literature, this ambitious book is sure to be an invaluable resource for all those to whom the terms unit roots, cointegration and error correction forms, ch
| Author | : Jianjun Miao |
| Publisher | : MIT Press |
| Total Pages | : 737 |
| Release | : 2014-09-19 |
| Genre | : Business & Economics |
| ISBN | : 0262325608 |
A unified, comprehensive, and up-to-date introduction to the analytical and numerical tools for solving dynamic economic problems. This book offers a unified, comprehensive, and up-to-date treatment of analytical and numerical tools for solving dynamic economic problems. The focus is on introducing recursive methods—an important part of every economist's set of tools—and readers will learn to apply recursive methods to a variety of dynamic economic problems. The book is notable for its combination of theoretical foundations and numerical methods. Each topic is first described in theoretical terms, with explicit definitions and rigorous proofs; numerical methods and computer codes to implement these methods follow. Drawing on the latest research, the book covers such cutting-edge topics as asset price bubbles, recursive utility, robust control, policy analysis in dynamic New Keynesian models with the zero lower bound on interest rates, and Bayesian estimation of dynamic stochastic general equilibrium (DSGE) models. The book first introduces the theory of dynamical systems and numerical methods for solving dynamical systems, and then discusses the theory and applications of dynamic optimization. The book goes on to treat equilibrium analysis, covering a variety of core macroeconomic models, and such additional topics as recursive utility (increasingly used in finance and macroeconomics), dynamic games, and recursive contracts. The book introduces Dynare, a widely used software platform for handling a range of economic models; readers will learn to use Dynare for numerically solving DSGE models and performing Bayesian estimation of DSGE models. Mathematical appendixes present all the necessary mathematical concepts and results. Matlab codes used to solve examples are indexed and downloadable from the book's website. A solutions manual for students is available for sale from the MIT Press; a downloadable instructor's manual is available to qualified instructors.
| Author | : Stephen P. Ellner |
| Publisher | : Princeton University Press |
| Total Pages | : 352 |
| Release | : 2011-09-19 |
| Genre | : Science |
| ISBN | : 1400840961 |
From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students in the biological sciences, ecologist Stephen Ellner and mathematician John Guckenheimer teach students how to understand, build, and use dynamic models in biology. Developed from a course taught by Ellner and Guckenheimer at Cornell University, the book is organized around biological applications, with mathematics and computing developed through case studies at the molecular, cellular, and population levels. The authors cover both simple analytic models--the sort usually found in mathematical biology texts--and the complex computational models now used by both biologists and mathematicians. Linked to a Web site with computer-lab materials and exercises, Dynamic Models in Biology is a major new introduction to dynamic models for students in the biological sciences, mathematics, and engineering.
| Author | : Gerhard Sorger |
| Publisher | : Cambridge University Press |
| Total Pages | : 453 |
| Release | : 2015-02-12 |
| Genre | : Business & Economics |
| ISBN | : 1316240843 |
Focusing on deterministic models in discrete time, this concise yet rigorous textbook provides a clear and systematic introduction to the theory and application of dynamic economic models. It guides students through the most popular model structures and solution concepts, from the simplest dynamic economic models through to complex problems of optimal policy design in dynamic general equilibrium frameworks. Chapters feature theorems and practical hints, and seventy-five worked examples highlight the various methods and results that can be applied in dynamic economic models. Notation and formulation is uniform throughout, so students can easily discern the similarities and differences between various model classes. Chapters include more than sixty exercises for students to self-test their analytical skills, and password-protected solutions are available for instructors on the companion website. Assuming no prior knowledge of dynamic economic analysis or dynamic optimization, this textbook is ideal for advanced students in economics.
| Author | : Mark M. Meerschaert |
| Publisher | : Elsevier |
| Total Pages | : 360 |
| Release | : 2007-06-18 |
| Genre | : Mathematics |
| ISBN | : 9780123708571 |
Mathematical Modeling, Third Edition is a general introduction to an increasingly crucial topic for today's mathematicians. Unlike textbooks focused on one kind of mathematical model, this book covers the broad spectrum of modeling problems, from optimization to dynamical systems to stochastic processes. Mathematical modeling is the link between mathematics and the rest of the world. Meerschaert shows how to refine a question, phrasing it in precise mathematical terms. Then he encourages students to reverse the process, translating the mathematical solution back into a comprehensible, useful answer to the original question. This textbook mirrors the process professionals must follow in solving complex problems. Each chapter in this book is followed by a set of challenging exercises. These exercises require significant effort on the part of the student, as well as a certain amount of creativity. Meerschaert did not invent the problems in this book--they are real problems, not designed to illustrate the use of any particular mathematical technique. Meerschaert's emphasis on principles and general techniques offers students the mathematical background they need to model problems in a wide range of disciplines. Increased support for instructors, including MATLAB material New sections on time series analysis and diffusion models Additional problems with international focus such as whale and dolphin populations, plus updated optimization problems
| Author | : Torsten Söderström |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 410 |
| Release | : 2002-07-26 |
| Genre | : Mathematics |
| ISBN | : 9781852336493 |
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 | : Rolf Isermann |
| Publisher | : Springer |
| Total Pages | : 705 |
| Release | : 2011-04-08 |
| Genre | : Technology & Engineering |
| ISBN | : 9783540871552 |
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.
| Author | : Tohru Ozaki |
| Publisher | : CRC Press |
| Total Pages | : 561 |
| Release | : 2012-01-26 |
| Genre | : Mathematics |
| ISBN | : 1420094610 |
Recent advances in brain science measurement technology have given researchers access to very large-scale time series data such as EEG/MEG data (20 to 100 dimensional) and fMRI (140,000 dimensional) data. To analyze such massive data, efficient computational and statistical methods are required.Time Series Modeling of Neuroscience Data shows how to
