Introduction to Optimal Estimation

Introduction to Optimal Estimation

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Developed from a set of lecture notes by Professor Kamen and since developed and refined by both authors, this introductory yet comprehensive study is a prime example in its field. There are examples in the book that use MATLAB® and many of the problems discussed require the use of MATLABâ. 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...