Purdue University
School of Electrical and Computer Engineering

EE641 Image Processing II
Prof. Charles A. Bouman

Homework 1: Chapter 2 (Probability), problems 1 to 5.

Homework 2: Chapter 2 (Probability), problems 5 to 20.

Homework 3: Chapter 3 (Causal Gaussian Models), problems 1 to 10.

Homework 4: Chapter 4 (Non-Causal Gaussian Models), problems 1 to 11.

Homework 5: Chapter 5 (MAP Estimation), problems 1 to 6.

Homework 6: Chapter 6 (Non-Gaussian MRFs), problems 1 to 6.

Homework 7: Chapter 7 (Non-Gaussian MAP), problems 1 to 6; and Chapter 8 (Surrogate Functions), problems 1 to 5.

Homework 8: Chapter 9 (Constrained Optimization), problems 1 to 10.

Homework 9: Chapter 10 (Plug-and-Play), problems 1 to 5.

Homework 10: Chapter 12 (EM Algorithm), problems 1 to 8.

Homework 11: Chapter 13 (MC and HMM), problems 1 to 7.

Homework 12: Chapter 15 (Stochastic Simmulation), problems 1 to 6.