INTRODUCTION TO OPTIMAL ESTIMATION.pdf

INTRODUCTION TO OPTIMAL ESTIMATION

Jonathan-K Su

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(r) and many of the problems discussed require the use of MATLAB(r). 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 maximum a posteriori estimation, based on discrete-time measurements. In the study of these estimation techniques there is a 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-Marquardt algorithm.

Full text of "An Introduction To Optimal Estimation" This banner text can have markup.. web; books; video; audio; software; images; Toggle navigation

8.14 MB Taille du fichier
9781852331337 ISBN
INTRODUCTION TO OPTIMAL ESTIMATION.pdf

Technik

PC et Mac

Lisez l'eBook immédiatement après l'avoir téléchargé via "Lire maintenant" dans votre navigateur ou avec le logiciel de lecture gratuit Adobe Digital Editions.

iOS & Android

Pour tablettes et smartphones: notre application de lecture tolino gratuite

eBook Reader

Téléchargez l'eBook directement sur le lecteur dans la boutique www.ferraricp.com.au ou transférez-le avec le logiciel gratuit Sony READER FOR PC / Mac ou Adobe Digital Editions.

Reader

Après la synchronisation automatique, ouvrez le livre électronique sur le lecteur ou transférez-le manuellement sur votre appareil tolino à l'aide du logiciel gratuit Adobe Digital Editions.

Notes actuelles

avatar
Sofya Voigtuh

INTRODUCTION TO OPTIMAL ESTIMATION 1ST EDITION PDF

avatar
Mattio Müllers

Cite this chapter as: Kamen E.W., Su J.K. (1999) Optimal Estimation. In: Introduction to Optimal Estimation. Advanced Textbooks in Control and Signal Processing. Optimal estimation - Wikipedia

avatar
Noels Schulzen

Introduction. The Kalman filter and the Kalman-Bucy filter [1, 2] solved the problem of optimal estimation of stochastic and deterministic linear systems.

avatar
Jason Leghmann

"An excellent introduction to optimal control and estimation theory and its relationship with LQG design. . . . invaluable as a reference for those already familiar ... estimator 0.0∗x1 + 1.0∗x2. Kalman filtering tells us that in general, this intuitively reasonable linear estimator is not. “optimal”; paradoxically, there is useful ...

avatar
Jessica Kolhmann

INTRODUCTION TO OPTIMAL ESTIMATION 1ST EDITION PDF