CMPS290D: Neural Computation

An introduction to the design and analysis of neural network algorithms. Concentrates on large artificial neural networks and their applications in pattern recognition, signal processing, and forecasting and control. Topics include Hopfield and Boltzmann machines, perceptions, multilayer feed forward nets, and multilayer recurrent networks. Enrollment restricted to graduate students.

5 credits

Year Fall Winter Spring Summer

While the information on this web site is usually the most up to date, in the event of a discrepancy please contact your adviser to confirm which information is correct.