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Note: This course is not available for the current semester.
Course No: 92.549; Last Offered: No Data;
Course Description
Signal processing and Fourier analysis fundamentals in one and several variables, deterministic algorithms for image reconstruction with non-diffracting sources, daling wiht noisy data and (briefly) the problem of diffracting sources, physically realistic statistical models for the data, the use of statistical parameter estimation as a reconstruction paradigm, likelihood maximization, the expectation maximization (EM) iterative algorithm, applications of the EM algorithm to emission and transmission tomography, controlling noise through Bayesian maximum a posteriori estimation, and acceleration of convergence using incremental optimization or block-iterative methods.
Prerequisites & Notes
- Prerequisites:
- Special Notes:
- Credits: 3;
Questions About This Course?
Contact the Advising Center at 978-934-2474 or
Continuing_Education@uml.edu
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