EE315 Probability & Random Processes for Engineers
Welcome to your EE315 Homepage. It is a pleasure to have you in this course.
A good start is needed. This course is very fundamental to many other courses and concepts in our life. Matlab will be an integrated part of the course. It will be mostly self-learning tool. Start today by installing Matlab in your machine or find yourself a convenient access to it. Some Videos are link below for full list of lectures visit my YouTube Channel.
I pray Allah that you will find this course fruitful and enjoyable.
Best Regards,
Dr. Ali Muqaibel
Class Notes:
1. Probability (Ch 1) (pdf)
2. Random Variables (Ch 2) (pdf)
Random Variables: definitions and Types (YouTube)
Random Variables CDF and pdf (YouTube)
Gaussian (Normal) R.V. (YouTube)
Gaussian R.V CDF and Q-Function Approximation (YouTube)
Binomial Distribution (Additional Examples of Random Variables) (YouTube)
Poisson, Uniform, Exponential, Rayleigh (Additional Important distributions) (YouTube)
Conditional Density (pdf) and Distribution (CDF) (YouTube)
Range Conditioned Density and Distribution Functions (YouTube)
3. Operation on One Random Variable (Ch3) (pdf)
Expectation (YouTube)
Moments (YouTube)
Chebyshev and Markov Inequalities (YouTube)
Characteristic and Moment Generating Functions (YouTube)
Transformation of Random Variables
4. Multiple Random Variables (Ch4) (pdf)
Introduction to Vectors of Random Variables and CDF (YouTube)
Joint distribution function (YouTube)
Joint density function and properties (YouTube)
Conditional distribution and density (YouTube)
Statistical Independence (YouTube)
Distribution and density of a sum of r.v.’s (YouTube)
Central Limit Theorem (Matlab Code) (YouTube)
5. Operation on Multiple Random Variables (pdf)
Expected value of a function of r. v.’s (Matlab Code) (YouTube)
Joint characteristic functions (YouTube)
Jointly Gaussian r. v.’s (Matlab Code, results) (YouTube)
Transformations of multiple r.v.’s (YouTube)
Linear transformations of Gaussian r.v.’s (YouTube)
Sampling and some limit theorems (YouTube)
6. Random Processes –Temporal Characteristics (pdf)
Concept of a random process (YouTube)
Stationary and independence (YouTube)
Correlation functions and their properties (YouTube)
Gaussian random process (YouTube)
Poisson random process (YouTube)
Time Averages and Ergodicity (YouTube)
Measurement of Correlation Function (YouTube)
7. Random Processes – Spectral Characteristic (pdf)
Power Spectral Density and its properties (YouTube)
Relationship between PSD and auto-correlation function (YouTube)
8. Linear systems with random inputs (pdf)
Random signal response of linear systems (YouTube)
Spectral characteristics of system response (YouTube)
9. REVIEW
Quizzes :
Additional Links:
EE315 is available as an online course