Computer Science and Engineering

CSE 290D 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. (Formerly Computer Science 290D.)

Requirements

Enrollment is restricted to graduate students.

Credits

5

Quarter offered

Fall

Instructor

Manfred Warmuth

Repeatable for credit

Yes