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Prerequisites: CSCI 210, MATH 231 and MATH 303. Offered Occasionally.
An introduction to basic concepts in the design, analysis, and application for computational neural networks. Mathematical models of biological neurons. Multilayer perceptrons backward error propagation. Hopfield networks and Boltzmann machines. Radial-basis function networks. Kohonen self-organizing feature maps. Adaptive Resonance Theory networks.
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