EEE 222 - Electronic Neural Networks

Institution:

California State University-Sacramento

Subject:

Description:

Current neural network architectures and electronic implementation of neural networks are presented. Basics of fuzzy logic is covered. Application software will be used to simulate training. Testing of various neural net architectures. Learning strategies such as back-propagation, Kohonen, Hopfield and Hamming algorithms will be explored. A final project requires the student to design, train and test a neural network for electronic implementation that solves a specific practical problem. Graded: Graded Student. Units: 3.0

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.csus.edu

Phone Number:

(916) 278-6011

Regional Accreditation:

Western Association of Schools and Colleges

Calendar System:

Semester

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