ELEC 4030E-4Z01/COMM 6008E-6001 Random Process 隨機程序 2010 Fall

ELEC 4030E-4Z01/COMM 6008E-6001

Random Process 隨機程序 2010 Fall Instructor: Hsiao-Ping Tsai

Email: hptsai@nchu.edu.twOffice: EE711 Phone: 886-4-22851549 ext.711

General Course Information Course Objective

The goal of the course is to introduce the subject of probability theory and stochastic processes in engineering

Classroom: EE208 Class Times: Tue. 2:10pm - 5:00pm Web site: 電機系首頁 -> 課程規章 -> 課程詳述 -> 隨機程序

http://www.ee.nchu.edu.tw/wb_course02.asp?yr=99&cc=2&sn=946

General Course Information (con’t) Instructor: 蔡曉萍 (Hsiao-Ping Tsai )

Office: EE711 Phone: (04)22851549 ext. 711 E-Mail: hptsai@nchu.edu.tw Office hours: Mon.14 ： 00 ~ 16 ： 00, Wed. 10 ： 00 ~ 12 ：

00

Teaching Assistant: 尤淑佩 , 尤淑佩 Office: EE 910 Phone: (04)22851549 ext. 910 Email: elaine51666@yahoo.com.tw, evelyn0903@yahoo.com.tw

General Course Information (con’t) Textbook

Sheldon M. Ross, Stochastic Processes 2nd ed. Wiley, 1996 ISBN ： 0471120626 國內代理： 歐亞書局

Reference book Roy D. Yates and David J. Goodman, Probability and Stochastic

Processes: A Friendly Introduction for Electrical and Computer Engineers 2nd ed.

A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Processes 4th ed.

Topics Covered

Basic concepts of probability and random variables (4 weeks)

Poisson process (2 weeks) Renewal theory (2 weeks) Markov chains (4 weeks) Martingales (2 weeks) Random walks (2 weeks) Others: Brownian motion and Other Markov

Processes (optional)

Topics Covered (con’t)

Basic concepts of probability and random variables Random Variable Probability and Expectations Probability Inequalities

Poisson Processes Introduction Properties Non-homogeneous Poisson Processes Compound Poisson Processes Poisson Arrival See Time Average (PASTA)

Topics Covered (con’t)

Renewal Processes Introduction Limit Theorems Key Renewal Theorems Renewal Reward Processes Delayed Renewal Processes Regenerative Processes

Discrete-Time Markov Chains Introduction Classification of States Markov Reward Processes Time- Reversible Markov Chains Semi-Markov Chains

Topics Covered (con’t)

Martingales Introduction Martingals Stopping Times Martingale convergence Theorem Azuma’s Inequality

Random walks Introduction Duality in Random Walks Remarks Concerning Exchangeable Random Walks G/G/1 Queues and Ruin Problems Blackwell’s Theorem

Grading

Exam I: 20% (10/12) Exam II: 20% (11/16) Exam III: 20% (12/21) Final Exam: 20% (1/18) Homework: 20%

Policies Late Policy: A homework must be turned in by the midnight of its

due day 5% of points will be deducted for each working day if a homework is turned

in late. A homework assignment will be counted as a Zero score once its solutions

are announced. Attendance Policy: Students are obligated to present in the class.

If you cannot present in the class, please ask for leave in advance. If a student is absent from class more than 3 times, he/she might lose the

chance of the grade adjustment at the end of the semester. Honesty Policy: Students are allowed to discuss problems with

their classmates (or me), but they must not blatantly copy others' solutions. A copying homework is graded zero point.

Assignment Submission: Students should submit their assignments through the ecampus system or to TA.