P: EE 600. Basic concepts in the design, analysis, and application of
computational neural networks. Highly parallel fine-grain architectural
models
such as the Boltzman machine, Rosenblatt's Perception, Hopfields' neural
nets, backpropogation, and their associated learning algorithms. Proposed
architectures and related simulation techniques. Applications to
signal/image processing and recognition, optimization, and controls.