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portada An Introduction to Optimal Estimation of Dynamical Systems
Type
Physical Book
Author
Publisher
Language
English
Pages
354
Format
Paperback
Dimensions
22.9 x 15.2 x 1.9 cm
Weight
0.48 kg.
ISBN13
9789400999220
Categories

An Introduction to Optimal Estimation of Dynamical Systems

J. L. Junkins (Author) · Springer · Paperback

An Introduction to Optimal Estimation of Dynamical Systems - Junkins, J. L.

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Synopsis "An Introduction to Optimal Estimation of Dynamical Systems"

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 to make a significant contribution toward minimizing the painful process most newcomers must go through in digesting and applying the theory. Thus the treatment 1s intro- ductory and essence-oriented rather than comprehensive. While some original material 1s included, the justification for this text lies not in the contribution of dramatic new theoretical re- sults, but rather in the degree of success I believe that I have achieved in providing a source from which this material may be learned more efficiently than through study of an existing text or the rather diffuse literature. This work is the outgrowth of the author's mid-1960's en- counter with the subject while motivated by practical problems aSSociated with space vehicle orbit determination and estimation of powered rocket trajectories. The text has evolved as lecture notes for short courses and seminars given to professionals at Pr>efaae various private laboratories and government agencies, and during the past six years, in conjunction with engineering courses taught at the University of Virginia. To motivate the reader's thinking, the structure of a typical estimation problem often assumes the following form: - Given a dynamical system, a mathematical model is hypothesized based upon the experience of the investigator.

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