More Books:

Introduction to Optimal Estimation
Language: en
Pages: 380
Authors: Edward W. Kamen, Jonathan K. Su
Categories: Technology & Engineering
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

A handy technical introduction to the latest theories and techniques of optimal estimation. It provides readers with extensive coverage of Wiener and Kalman filtering along with a development of least squares estimation, maximum likelihood and maximum a posteriori estimation based on discrete-time measurements. Much emphasis is placed on how they
An introduction to optimal estimation of dynamical systems
Language: en
Pages: 354
Authors: J.L. Junkins
Categories: Science
Type: BOOK - Published: 2012-02-12 - Publisher: Springer

This text 1s designed to introduce the fundamentals of esti mation to engineers, scientists, and applied mathematicians. The level of the presentation should be accessible to senior under graduates and should prove especially well-suited as a self study guide for practicing professionals. My primary motivation for writing this book 1s
An Introduction to Optimal Estimation
Language: en
Pages: 273
Authors: Paul B. Liebelt
Categories: Estimation theory
Type: BOOK - Published: 1967 - Publisher:

Books about An Introduction to Optimal Estimation
Optimal Estimation
Language: en
Pages: 376
Authors: Frank L. Lewis
Categories: Technology & Engineering
Type: BOOK - Published: 1986 - Publisher: Wiley-Interscience

Describes the use of optimal control and estimation in the design of robots, controlled mechanisms, and navigation and guidance systems. Covers control theory specifically for students with minimal background in probability theory. Presents optimal estimation theory as a tutorial with a direct, well-organized approach and a parallel treatment of discrete
Introduction to Optimal Estimation
Language: en
Pages: 380
Authors: Edward W. Kamen, Jonathan K. Su
Categories: Technology & Engineering
Type: BOOK - Published: 2011-10-06 - Publisher: Springer

A handy technical introduction to the latest theories and techniques of optimal estimation. It provides readers with extensive coverage of Wiener and Kalman filtering along with a development of least squares estimation, maximum likelihood and maximum a posteriori estimation based on discrete-time measurements. Much emphasis is placed on how they