ECE 503: Probability and Random Processes for Engineering

Applications – Fall 2016

• Instructor: Dr. Ravi Tandon

• E-mail: tandonr@email.arizona.edu

• Contact: 520-626-9627 (Office)

• Lecture Timing and Location: M, W, F 11:00am-11:50am, R. P. Harvill Building, Room 102.

• Office Hours: Monday 1:30pm-3:30pm (ECE 359) (Additional office hours by appointment)

• Textbook: A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Processes, 4thEdition, McGraw-Hill. (ISBN 978-0-07-366011-0)

• Reference Books:

– G. R. Grimmett and D. R. Stirzaker, Probability and Random Processes, Oxford University Press,3rd Edition.

– H. Stark and J. W. Woods, Probability and Random Processes with Applications to Signal Processing,Prentice Hall, 3rd Edition.

– John Gubner, Probability and Random Processes for Electrical and Computer Engineers, CambridgeUniversity Press, 2006.

• Recommended study habits: Attend the lectures, take notes, ask questions and do your homework.After some lectures, I will also point out specific material for supplemental reading.

• Grading:

– Homework (20%) - A total of 8-10 homeworks; each homework will be due in 1 week.

– Mid-term 1 (25%) - Date: TBD, (in class)

– Mid-term 2 (25%) - Date: TBD, (in class)

– Final Exam (30%) - Date: Wednesday, December 14, 2016 (10:30am - 12:30pm)

• Homework Submission: All homeworks and lectures will be posted on D2L (https://d2l.arizona.edu/).Mode of submission of HWs: submit in my mailbox (2nd floor, ECE Building).

Syllabus

1. Overview of Probability

• Axioms of Probability

• Bayes Rule, Conditional Probability

• Repeated Trials

2. Random Variables

• Concept of a Random Variable

• Distribution and Density Functions

• Commonly encountered random variables

• Conditional Distributions

• Function of a random variable

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• Mean and Variance, Moments

• Characteristic Functions

3. Two/More Random Variables

• Bivariate Distributions

• Joint moments, characteristic functions

• Conditional distributions, expectation, independence

• Mean Square Estimation

• Modes of Convergence, Weak Law of Large Numbers, Central Limit Theorem

4. Stochastic Processes

• General concepts

• Types of Stationarity

• Properties of random processes

• Poisson Processes

5. Markov Chains

• Introduction

• Discrete Time Markov Chains

• Classification of States

• Transition probabilities

• Stationary distributions and Limiting probabilities

• Student Code of Academic Integrity

Students are encouraged to share intellectual views and discuss freely the principles and applications ofcourse materials. However, homeworks must be the product of independent effort unless otherwiseinstructed. Students are expected to adhere to the UA Code of Academic Integrity as described in theUA General Catalog. See: http://deanofstudents.arizona.edu/codeofacademicintegrity/.

• Accessibility and Accommodations:

It is the University’s goal that learning experiences be as accessible as possible. If you anticipate orexperience physical or academic barriers based on disability or pregnancy, please let me know immediatelyso that we can discuss options. You are also welcome to contact Disability Resources (520-621-3268) toestablish reasonable accommodations.

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