Lecture Notes in Economics and Mathematical Systems
Author : A. V. Balakrishnan
Publisher :
Page : pages
File Size : 43,63 MB
Release : 1973
Category : Control theory
ISBN : 9780387063034
Author : A. V. Balakrishnan
Publisher :
Page : pages
File Size : 43,63 MB
Release : 1973
Category : Control theory
ISBN : 9780387063034
Author : Simo Särkkä
Publisher : Cambridge University Press
Page : 327 pages
File Size : 20,42 MB
Release : 2019-05-02
Category : Business & Economics
ISBN : 1316510085
With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.
Author : Andrew H. Jazwinski
Publisher : Courier Corporation
Page : 404 pages
File Size : 46,39 MB
Release : 2013-04-15
Category : Science
ISBN : 0486318192
This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well. Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probability theory and stochastic processes, the author introduces and defines the problems of filtering, prediction, and smoothing. He presents the mathematical solutions to nonlinear filtering problems, and he specializes the nonlinear theory to linear problems. The final chapters deal with applications, addressing the development of approximate nonlinear filters, and presenting a critical analysis of their performance.
Author : V. S. Pugachev
Publisher :
Page : 584 pages
File Size : 17,40 MB
Release : 1987-06-22
Category : Mathematics
ISBN :
Gives applied methods for studying stochastic differential systems--in particular, the methods for finding the finite-dimensional distributions of the state vector and of the output of such systems, and also the estimation methods of the state and of the parameters of differential systems based on observations (filtering and extrapolation theory). Also studied are stochastic differential equations of general type with arbitrary processes and independent increments. The equations with Wiener processes are considered as a special case. The construction of stochastic differential systems in the book is based on Pugachev's equations for finite-dimensional characteristic functions of the processes determined by stochastic differential equations. Includes end-of-chapter problems.
Author : Boris L. Rozovsky
Publisher : Springer
Page : 340 pages
File Size : 38,81 MB
Release : 2018-10-03
Category : Mathematics
ISBN : 3319948938
This monograph, now in a thoroughly revised second edition, develops the theory of stochastic calculus in Hilbert spaces and applies the results to the study of generalized solutions of stochastic parabolic equations. The emphasis lies on second-order stochastic parabolic equations and their connection to random dynamical systems. The authors further explore applications to the theory of optimal non-linear filtering, prediction, and smoothing of partially observed diffusion processes. The new edition now also includes a chapter on chaos expansion for linear stochastic evolution systems. This book will appeal to anyone working in disciplines that require tools from stochastic analysis and PDEs, including pure mathematics, financial mathematics, engineering and physics.
Author : Rong SITU
Publisher : Springer Science & Business Media
Page : 444 pages
File Size : 30,78 MB
Release : 2006-05-06
Category : Technology & Engineering
ISBN : 0387251758
Stochastic differential equations (SDEs) are a powerful tool in science, mathematics, economics and finance. This book will help the reader to master the basic theory and learn some applications of SDEs. In particular, the reader will be provided with the backward SDE technique for use in research when considering financial problems in the market, and with the reflecting SDE technique to enable study of optimal stochastic population control problems. These two techniques are powerful and efficient, and can also be applied to research in many other problems in nature, science and elsewhere.
Author : Bernt Oksendal
Publisher : Springer Science & Business Media
Page : 218 pages
File Size : 37,62 MB
Release : 2013-03-09
Category : Mathematics
ISBN : 3662130505
These notes are based on a postgraduate course I gave on stochastic differential equations at Edinburgh University in the spring 1982. No previous knowledge about the subject was assumed, but the presen tation is based on some background in measure theory. There are several reasons why one should learn more about stochastic differential equations: They have a wide range of applica tions outside mathematics, there are many fruitful connections to other mathematical disciplines and the subject has a rapidly develop ing life of its own as a fascinating research field with many interesting unanswered questions. Unfortunately most of the literature about stochastic differential equations seems to place so much emphasis on rigor and complete ness that is scares many nonexperts away. These notes are an attempt to approach the subject from the nonexpert point of view: Not knowing anything (except rumours, maybe) about a subject to start with, what would I like to know first of all? My answer would be: 1) In what situations does the subject arise? 2) What are its essential features? 3) What are the applications and the connections to other fields? I would not be so interested in the proof of the most general case, but rather in an easier proof of a special case, which may give just as much of the basic idea in the argument. And I would be willing to believe some basic results without proof (at first stage, anyway) in order to have time for some more basic applications.
Author : Alan Bain
Publisher : Springer Science & Business Media
Page : 395 pages
File Size : 11,82 MB
Release : 2008-10-08
Category : Mathematics
ISBN : 0387768963
This book provides a rigorous mathematical treatment of the non-linear stochastic filtering problem using modern methods. Particular emphasis is placed on the theoretical analysis of numerical methods for the solution of the filtering problem via particle methods. The book should provide sufficient background to enable study of the recent literature. While no prior knowledge of stochastic filtering is required, readers are assumed to be familiar with measure theory, probability theory and the basics of stochastic processes. Most of the technical results that are required are stated and proved in the appendices. Exercises and solutions are included.
Author : Jie Xiong
Publisher : Oxford University Press
Page : 285 pages
File Size : 45,95 MB
Release : 2008-04-17
Category : Business & Economics
ISBN : 0199219702
Stochastic Filtering Theory uses probability tools to estimate unobservable stochastic processes that arise in many applied fields including communication, target-tracking, and mathematical finance.As a topic, Stochastic Filtering Theory has progressed rapidly in recent years. For example, the (branching) particle system representation of the optimal filter has been extensively studied to seek more effective numerical approximations of the optimal filter; the stability of the filter with "incorrect" initial state, as well as the long-term behavior of the optimal filter, has attracted the attention of many researchers; and although still in its infancy, the study of singular filteringmodels has yielded exciting results.In this text, Jie Xiong introduces the reader to the basics of Stochastic Filtering Theory before covering these key recent advances. The text is written in a style suitable for graduates in mathematics and engineering with a background in basic probability.
Author : Samuel N. Cohen
Publisher : Springer Nature
Page : 303 pages
File Size : 14,48 MB
Release : 2019-08-31
Category : Mathematics
ISBN : 3030222853
This collection of selected, revised and extended contributions resulted from a Workshop on BSDEs, SPDEs and their Applications that took place in Edinburgh, Scotland, July 2017 and included the 8th World Symposium on BSDEs. The volume addresses recent advances involving backward stochastic differential equations (BSDEs) and stochastic partial differential equations (SPDEs). These equations are of fundamental importance in modelling of biological, physical and economic systems, and underpin many problems in control of random systems, mathematical finance, stochastic filtering and data assimilation. The papers in this volume seek to understand these equations, and to use them to build our understanding in other areas of mathematics. This volume will be of interest to those working at the forefront of modern probability theory, both established researchers and graduate students.