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Introduction to Optimal Estimation

  • E. W. Kamen
  • J. K. Su

Table of contents

  1. Front Matter
    Pages I-XIII
  2. E. W. Kamen, J. K. Su
    Pages 1-26
  3. E. W. Kamen, J. K. Su
    Pages 27-68
  4. E. W. Kamen, J. K. Su
    Pages 69-100
  5. E. W. Kamen, J. K. Su
    Pages 101-147
  6. E. W. Kamen, J. K. Su
    Pages 149-189
  7. E. W. Kamen, J. K. Su
    Pages 191-223
  8. E. W. Kamen, J. K. Su
    Pages 225-267
  9. E. W. Kamen, J. K. Su
    Pages 269-311
  10. Back Matter
    Pages 313-380

About this book

Introduction

This book, developed from a set of lecture notes by Professor Kamen, and since expanded and refined by both authors, is an introductory yet comprehensive study of its field. It contains examples that use MATLAB® and many of the problems discussed require the use of MATLAB®. The primary objective is to provide students with an extensive coverage of Wiener and Kalman filtering along with the development of least squares estimation, maximum likelihood estimation and a posteriori estimation, based on discrete-time measurements. In the study of these estimation techniques there is strong emphasis on how they interrelate and fit together to form a systematic development of optimal estimation. Also included in the text is a chapter on nonlinear filtering, focusing on the extended Kalman filter and a recently-developed nonlinear estimator based on a block-form version of the Levenberg-Marquadt Algorithm.

Keywords

Signal Software Theorie algorithm development model modeling

Authors and affiliations

  • E. W. Kamen
    • 1
  • J. K. Su
    • 2
  1. 1.School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaUSA
  2. 2.Telecommunications LaboratoryUniversity of Erlangen-NurnbergErlangenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-0417-9
  • Copyright Information Springer-Verlag London Limited 1999
  • Publisher Name Springer, London
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-85233-133-7
  • Online ISBN 978-1-4471-0417-9
  • Series Print ISSN 1439-2232
  • Series Online ISSN 2510-3814
  • Buy this book on publisher's site
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