ECE 5535 - Math Neuro Methods

Institution:

University of Utah

Subject:

Electrical and Computer Engineering

Description:

Course covers a set of mathematical and statistical methods that are fundamental for analyzing and modeling neural/cognitive data and neural signal and information processing, practiced through extensive computational exercises. Topics include linear algebra, least-squares regression, eigen-analysis and PCA, linear shift-invariant systems, convolution, Fourier transforms, Nyquist sampling, basics of probability and statistics, hypothesis testing, model comparison, bootstrapping, estimation and decision theory, signal detection theory, classification, linear discriminants, clustering, simple models of neural spike generation, analysis. Intended for students from quantitative backgrounds, i.e. engineering, math, statistics, computer science, physics, neuroscience, psychology. Prerequisites: NOT on ECE Monitoring Group Corequisites: ECE 5836 OR ECE 6836

Credits:

3.00 - 4.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.utah.edu

Phone Number:

(801) 581-7200

Regional Accreditation:

Northwest Commission on Colleges and Universities

Calendar System:

Semester

General Education

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