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
Session | Section | Class # | Type | Days | Time | Location | Instructor | Course Details [Key] |
---|---|---|---|---|---|---|---|---|
E1 | 1 | 2292 | LEC | TH | 06:00 PM - 09:00 PM | Sierra Hall 1242 | Vedang Chauhan |
![]() ![]() ![]() ![]() |
Key for Course Detail Icons
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |