ICsi 451 - Bayesian Data Analysis and Signal Processing

Institution:

SUNY at Albany

Subject:

Description:

This course will introduce both the principles and practice of Bayesian and maximum entropy methods for data analysis, signal processing, and machine learning. This is a hands-on course that will introduce the use of the MATLAB computing language for software development. Students will learn to write their own Bayesian computer programs to solve problems relevant to physics, chemistry, biology, earth science, and signal processing, as well as hypothesis testing and error analysis. Optimization techniques to be covered include gradient ascent, fixed-point methods, and Markov chain Monte Carlo sampling techniques.? Only one of I Inf 451, I Csi 451, or A Phy 451 may be taken for credit. Prerequisite(s): A Mat 214 (or equivalent) and I Csi 101 or I Csi 201.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.albany.edu

Phone Number:

(518) 442-3300

Regional Accreditation:

Middle States Association of Colleges and Schools

Calendar System:

Semester

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