Skip to main content
Book cover

Estimation and Control Problems for Stochastic Partial Differential Equations

  • Book
  • © 2013

Overview

  • Investigates important aspects of estimation and control theory for systems modeled by stochastic partial differential equations
  • Presents research on problems of estimation and control theory for random fields that has not been previously covered by researchers
  • Includes research on control, prediction, and estimation for systems with two parameters and additive noise
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Optimization and Its Applications (SOIA, volume 83)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (5 chapters)

Keywords

About this book

Focusing on research surrounding aspects of insufficiently studied problems of estimation and optimal control of random fields, this book exposes some important aspects of those fields for systems modeled by stochastic partial differential equations. It contains many results of interest to specialists in both the theory of random fields and optimal control theory who use modern mathematical tools for resolving specific applied problems, and presents research that has not previously been covered. More generally, this book is intended for scientists, graduate, and post-graduates specializing in probability theory and mathematical statistics.

The models presented describe many processes in turbulence theory, fluid mechanics, hydrology, astronomy, and meteorology, and are widely used in pattern recognition theory and parameter identification of stochastic systems. Therefore, this book may also be useful to applied mathematicians who use probability and statistical methods in the selection of useful signals subject to noise, hypothesis distinguishing, distributed parameter systems optimal control, and more. Material presented in this monograph can be used for education courses on the estimation and control theory of random fields.

Reviews

From the book reviews:

“The book is focused on the study of stochastic (partial) differential equations of hyperbolic type. … there are several topics treated in the book that may be of interest to specialists working in stochastic multiparameter SDEs and SPDEs, especially for those interested in problems of control and filtering.” (Bohdan Maslowski, Mathematical Reviews, February, 2015)

Authors and Affiliations

  • National Academy of Sciences of Ukraine VM Glushkov Institute of Cybernetics, Kiev, Ukraine

    Pavel S. Knopov

  • Dept. of Math. Methods of Operation Rese, National Acadamy of Sciences of Ukraine V.M. Glushkov Institute of Cybernetics, Kiev, Ukraine

    Olena N. Deriyeva

Bibliographic Information

Publish with us