COMP 572 - Neural Networks
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Description
Hours: Three hours lecture in the lab per week Prerequisites: Admission to the Computer Science or Mathematics Graduate Program Covers the basic ideas of distributed computation with many simple processing units, similar to the neurons of the brain. Topics include: Hopfield style networks applied to optimization problems, and the backpropagation method applied to pattern classification problems. Additional topics include associate memory, binary vs. analog networks, simulated annealing.
Units: 3.00
Grading: Letter Grade
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