### EE 325 – PROBABILITY AND RANDOM PROCESSES

**Semester –**

Autumn 2017

**Prerequisites:**
EE-223- Data analysis and interpretation

**Motivation –**

Probability and random processes is integral to many scientific disciplines including machine learning, communications and even economics and finance. Understanding this course would give you a solid background to many other statistical courses.

**Course Content –**

Review of classical probability; axioms of probability; Review of set theory, Infinite sets; Fields; Conditional probability and independence; Continuous, discrete and other Random variables; Cumulative distribution functions; Conditional distributions; Functions of random variables; Random vectors; Joint normal distributions; Inequalities; Characteristic functions; Random sequences and their convergence; Random Processes: basics, stationary processes, mean correlation and covariance functions, ergodicity, through LTI systems, Power spectral density, Gaussian processes, Noise

**Lectures –**

The lectures were extremely well structured and organized. All the concepts were well explained by the professor. The professor was very receptive to doubts but wasn’t inherently interactive. Some concepts were trickier and a bit harder to understand so pay attention at those times and do ask doubts if its still not clear. Slides were uploaded immediately after lectures.

**Attendance –**

Attendance was taken every lecture manually but the overall the attendance was still low. Nobody was penalized for low attendance, but it is still necessary to attend lectures as the course is a little hard to grasp.

**Exams –**

The question papers were balanced with a mix of easy and difficult questions. If you solve the assignments regularly, you’ll fair through easily.

- 20% Quizzes (best 2 of 3, 10 marks each covering 1/3 of the syllabus)
- 30% Midsem (30 marks)
- 50% Endsem (50 marks)

**Reference Books:**

- Probability, Random Variables and Stochastic Processes, Papoulis
- Probability and Random Processes with Applications to Signal Processing, Stark and Woods
- Communication Systems 4th Edition, Haykin