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Estimation and Control Problems for Stochastic Partial Differential Equations: Springer Optimization and Its Applications, cartea 83

Autor Pavel S. Knopov, Olena N. Deriyeva
en Limba Engleză Hardback – 18 sep 2013
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.
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Specificații

ISBN-13: 9781461482857
ISBN-10: 1461482852
Pagini: 196
Ilustrații: X, 183 p.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.45 kg
Ediția:2013
Editura: Springer
Colecția Springer
Seria Springer Optimization and Its Applications

Locul publicării:New York, NY, United States

Public țintă

Research

Cuprins

1. Two Parameter Martingales and Their Properties.- 2. Stochastic Differential Equations on the Plane.- 3. Filtration and Prediction Problems for Stochastic Fields.- 4. Control Problem for Diffusion-Type Random Fields.- 5. Stochastic Processes in a Hilbert Space.- References.

Recenzii

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)

Textul de pe ultima copertă

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.

Caracteristici

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