CS 5300 - Artificial Neural Systems

An introduction to neural net concepts, algorithms, and applications. A history of neural nets will be presented along with some discussion of models of Biological neural systems. The salient features of neural nets (architecture, activation functions, weighting scheme) will be characterized. Standard algorithms will be presented including Hopfield nets, linear associative mode bidirectional associative memories, and adaptive resonance models. The student will use neural net software to experiment with standard models to develop an application for a project.

Note: An introductory statistics course is recommended. Open to upper-level undergraduate and graduate students.

Prerequisites & Corequisites: Prerequisite: CS 3310

Credits: 3 hours