ECE 302: Probabilistic Methods in Electrical and Computer Engineering

Fall 2018
Professor Stanley H. Chan

Course Notes

Note that all course materials are copyrighted. Without permission of Prof Chan, students are not allowed to redistribute the materials, including note, homework, projects and exams.

Additional Course Note

Lecture Slides

  • 08-21-2018 Lecture 00: Introduction

  • 08-21-2018 Lecture 00 Supplementary: Installing Python

  • 08-21-2018 Lecture 01: Series

  • 08-23-2018 Lecture 02: Approximation, Integration, Linear Algebra, Set Theory

  • 08-28-2018 Lecture 03: Set Theory, Combinatorics

  • 08-30-2018 Lecture 04: Probability Model, Sample Sapce, Event Space, Axioms

  • 09-04-2018 Lecture 05: Conditional Probabilities

  • 09-06-2018 Lecture 06: Bayes Theorem, Law of Total Probability

  • 09-11-2018 Lecture 07: Probability Mass Function, Expectation

  • 09-13-2018 Lecture 08: Variance, CDF, Bernoulli

  • 09-18-2018 Lecture 09: Bernoulli, Binomial, Geometric, Poisson

  • 09-20-2018 Lecture 10: Poisson, Generating random variable, CDF, Project 1 Discussion

  • 09-25-2018 Lecture 11: PDF, Expectation, Variance, Uniform, Exponential

  • 09-27-2018 Lecture 12: CDF, Gaussian distribution

  • 10-02-2018 Lecture 13: Gaussian, function of random variable

  • 10-11-2018 Lecture 14: Joint PMF, PDF, CDF, Conditional

  • 10-16-2018 Lecture 15: Joint Expectation, Correlation, Conditional Expectation

  • 10-18-2018 Lecture 16: Conditional Expectation

  • 10-23-2018 Lecture 17: Sum of Two Random Variables

  • 10-25-2018 Lecture 18: Joint Gaussian

  • 10-30-2018 Lecture 19: Classification using Joint Gaussians

  • 11-01-2018 Lecture 20: Moment Generating Function

  • 11-06-2018 Lecture 21: Characteristic Function, Law of Large Number

  • 11-13-2018 Lecture 22: Law of Large Number, Central Limit Theorem

  • 11-15-2018 Lecture 23: Intro to random process

  • 11-29-2018 Lecture 24: Auto-correlation, power spectral density

  • 12-06-2018 Lecture 26: Conclusion