Stochastic Processes
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- Last Updated: Monday, 16 January 2023 06:01
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Course Name: Stochastic Processes
Instructor: Dr. Afrooz Haghbin
Level: Graduate
Course Meeting Times: 3 Hours / Week
Prerequisites: Probability and Statistics in Engineering.
Course Description
In this course, we introduce the stochastic processes and the mathematical principles required to discuss them are presented.
Course Syllabus
1- A Review on Probability and Statistics
2- Fundamentals of Stochastic Processes
3- Power Spectrum of Stochastic Processes
4- Orthogonal Expansion of Stochastic processes
5- Band-limited Stochastic Processes
6- Discrete Time Stochastic Processes
7- Estimation (if time permit)
Course Evaluation
Midterm Exam 40%
Final Exam 45%
Homework 15%
References
[1] A. Papoulis, S. U. Pillai, Probability, Random Variables and Stochastic Processes. 4th Edition, McGraw Hill, 2002.
[2] S. M. Ross, Introduction to Probability Models. 4th Edition, Academic Press, 2003.
[3] S. M. Ross, Stochastic processes. Wiley, New York, 1996.
[4] W.B. Davenport, Probability and Random Processes. McGraw Hill, 1970.
Lecture Notes 1401-1402 (Fall)
Lecture Notes 1400-1401 (Fall)
Lecture Notes 99-1400 (Fall)
Lecture Notes 98-99 (Fall)
Lecture Notes 97-98 (Fall)
Lecture Notes 96-97 (Fall)
Lecture Notes 95- 96 (Fall)
Lecture Notes 94-95 (Spring)
Lecture Notes 94-95 (Fall)
Lecture Notes 93-94 (Spring)
Homeworks
1- Homework No. 1. Download
2- Homework No. 2. Download
3- Homework No. 3. As defined in class
4- Homework No. 4. Download
5- Homework No. 5. As defined in class
6- Homework No. 6. As defined in class
7- Homework No. 7. Download
8- Homework No. 8. Download
9- Homework No. 9. As defined in class
Sample Midterm Download
Sample Final Download