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Birkhäuser

Partially Observable Linear Systems Under Dependent Noises

  • Book
  • © 2003

Overview

  • First monograph concentrating on dependent noises in linear systems and extensively discussing the infinite-dimensional case
  • Many applications in engineering
  • Valuable as a reference manual on functional analysis needed in systems theory
  • Includes supplementary material: sn.pub/extras

Part of the book series: Systems & Control: Foundations & Applications (SCFA)

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Table of contents (12 chapters)

Keywords

About this book

Noise is a rich concept playing an underlying role in human activity. Consideration of the noise phenomenon in arts and sciences, respectively, makes the distinction between both domains more obvious. Artists create "deliberate noise"`; the masterpieces of literature, music, modern fine art etc. are those where a clear idea, traditionally related to such concepts as love, is presented under a skilful veil of "deliberate noise". On the contrary, sciences fight against noise; a scientific discovery is a law of nature extracted from a noisy medium and refined.

This book discusses the methods of fighting against noise. It can be regarded as a mathematical view of specific engineering problems with known and new methods of control and estimation in noisy media.

The main feature of this book is the investigation of stochastic optimal control and estimation problems with the noise processes acting dependently on the state (or signal) and observation systems. While multiple early and recent findings on the subject have been obtained and challenging problems remain to be solved, this subject has not yet been dealt with systematically nor properly investigated. The discussion is given for infinite dimensional systems, but within the linear quadratic framework for continuous and finite time horizon. In order to make this book self-contained, some background material is provided.

Consequently, the target readers of this book are both applied mathematicians and theoretically oriented engineers who are designing new technology, as well as students of the related branches. The book may also be used as a reference manual in that part of functional analysis that is needed for problems of infinite dimensional linear systems theory.

Reviews

"The book is very well and carefully written. It is an excellent reference on the complete sets of equations for the optimal controls and for the optimal filters under wide band noises and shifted white noises and their possible application to navigation of spacecraft. Independently, it can serve as a useful reference on the part of functional analysis that is needed for problems of infinite-dimensional linear systems theory. The book is written for both applied mathematicians and theoretically oriented engineers as well as for students at a graduate level. The control community will find this reference an important contribution to the modern control and estimation theory literature."

—Mathematical Reviews

"This book deals with key issues in control theory, namely the interaction between optimal control and observation and/or estimation issues…. The book…will be of interest to researchers in optimal control and estimation."

—Zentralblatt Math

Authors and Affiliations

  • Department of Mathematics, Eastern Mediterranean University, Mersin 10, Turkey

    Agamirza E. Bashirov

Bibliographic Information

  • Book Title: Partially Observable Linear Systems Under Dependent Noises

  • Authors: Agamirza E. Bashirov

  • Series Title: Systems & Control: Foundations & Applications

  • DOI: https://doi.org/10.1007/978-3-0348-8022-0

  • Publisher: Birkhäuser Basel

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Basel AG 2003

  • Hardcover ISBN: 978-3-7643-6999-6Published: 23 January 2003

  • Softcover ISBN: 978-3-0348-9407-4Published: 05 November 2012

  • eBook ISBN: 978-3-0348-8022-0Published: 06 December 2012

  • Series ISSN: 2324-9749

  • Series E-ISSN: 2324-9757

  • Edition Number: 1

  • Number of Pages: XXVI, 338

  • Topics: Systems Theory, Control

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