Week 6: Stochastic Processes + Parameter Estimation

This week, I finish Section 2.7 (about stochastic processes) initiated in Week 5 and fully present Chapter 3, which is about parameter estimation. This chapter is very important, since the notation and estimation criteria adopted here (particularly the Bayesian ones) will be almost directly applied to the formulation of optimal filters from Chapter 4 on.

Material:

• Section 2.7: Stochastic Processes
• Chapter 3: Parameter Estimation
• Computational Exercise #1

Previous post of this course:

• Week 1: Syllabus + Introduction
• Week 2: Linear Algebra + Linear Systems
• Week 3: Set + Probability + Random Variables
• Week 4: Random Variables + Random Vectors
• Week 5: Random Vectors + Stochastic Processes