» MIT OpenCourseWare » Brain and Cognitive Sciences » Introduction to Neural Networks, Fall 2002

Assignments

This section is an overview of all the problem sets for this course. Several example problem sets are provided here. However, most of the problems cannot be done without access to MATLAB® and special computers.

Problem Set 1. Integrate-and-Fire Neurons. (PDF)
Problem Set 2. Simple Perceptrons and Gradient Descent.
Problem Set 3. Multilayer Perceptrons and Backpropagation.
Problem Set 4. Statistical Learning Theory. (PDF)
Problem Set 5. PCA and Linear Networks. (PDF)
Problem Set 6. Nonlinear Network Theory. (PDF)
Problem Set 7. Nonlinear Network Theory again.
Problem Set 8. VQ and Lyapunov.
Problem Set 9. Models of Associative Memory.
Problem Set 10. Neural Integrators and Contrastive Hebbian Learning.
Problem Set 11. Reinforcement and Trajectory Learning.

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Assignments