Intro to Neural Networks
ECE 62900/ 3 Cr.
An introduction to basic concepts in the design, analysis, and application for computational neural networks. Topics include highly parallel fine grain architectural models such as the Boltzmann machine, Rosenblatt's Perception, Hopfields' neural nets, backpropogation, and their associated learning algorithms. Proposed architectures and related simulation techniques are discussed. Applications to signal/image processing and recognition, optimization, and controls are examined.
- Available Online: No
- Credit by Exam: No
- Laptop Required: No
