Lecture Notes

Lec # Topics
1 From Spikes to Rates (PDF)
2 Perceptrons: Simple and Multilayer
3 Perceptrons as Models of Vision
4 Linear Networks
5 Retina
6 Lateral Inhibition and Feature Selectivity (PDF 1) (PDF 2) (PDF 3)
7 Objectives and Optimization
8 Hybrid Analog-Digital Computation

Ring Network
9 Constraint Satisfaction

Stereopsis
10 Bidirectional Perception
11 Signal Reconstruction
12 Hamiltonian Dynamics (PDF)
13 Antisymmetric Networks (PDF)
14 Excitatory-Inhibitory Networks (PDF)

Learning
15 Associative Memory
16 Models of Delay Activity

Integrators
17 Multistability

Clustering
18 VQ (PDF)

PCA (PDF)
19 More PCA

Delta Rule (PDF)
20 Conditioning (PDF)

Backpropagation (PDF)
21 More Backpropagation (PDF)
22 Stochastic Gradient Descent
23 Reinforcement Learning
24 More Reinforcement Learning
25 Final Review