LoginEstimation Theory
(ECTS: 3; SWS: 2)Lecturers
Prof. Dr. Richard Bamler, Dr.-Ing. Stefan Gernhardt| prerequisites | complex calculus, signal processing, linear algebra, integrals | |
| objectives | The goal of this course is to deliver insight into basic and advanced techniques of decision making and estimation processes with emphasis on remote sensing applications. A theoretical understanding of the influence of prior knowledge, measurements and models will be given and demonstrated with simplified examples. Fundamental limits of estimation procedures will be understood. | |
| contents | Statistical Basics, Bayes' Theorem, Detection, Courseification, Parameter Estimation, Time and Frequency Estimation, Multi-Parameter Estimation (Optimal Estimation), Model Selection, Tracking Algorithms (Kalman Filter, Particle Filters), Signal Reconstruction from Irregular Sampling | |
| literature | There is not a dedicated book accompanying the lecture. The following two books, however, cover essential parts: Sivia, D.S., Data Analysis: A Bayesian Tutorial, Oxford Science Publications, 1996. Rodgers, C. D., Inverse methods for atmospheric sounding: Theory and practice, World Science, London, 2000. |
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