Course Information for 6500 - Mathematics of Imaging
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Primary Instructor: Sarang Joshi
Credits: 3.0
Semesters Offered:Spring
Frequency Offered:Annual
Catalog Description: Mathematical foundations of imaging, inluding linear systems, probability and random variables, and detection and estimation theory. Topics in linear systems include convolution, Fourier series and transformations, sampling and discrete-time processing. Topics in probability and random variables include distribution functions, density functions, expectations, means, variances, combinatorial probablility, joint distributions, independence, correlation, Bayes theorem, the law of large numbers, and the central limit theorem.
Course Syllabus:none