課程大綱

課程資訊
學年期 Semester	1142	課程代碼 Course Code	IM7102701
課程名稱 Course Title	隨機過程 Stochastic Processes
學分數 Credits	3	選必修 Required/Elective	選修 /半學年
上課時間教室 Time/Location	W2(MA-417) W3(MA-417) W4(MA-417)
先修課程 Prerequisite(s)
授課教師 Lecturer	郭伯勳 Po-Hsun Kuo
專業核心能力 Core Professional Competencies

以下課程內容資料由授課教師提供
課程相關網址 Course Website	http://
課程宗旨 Objective of The Course	Introduction to stochastic models and their applications: (a) Discrete-time and continuous-time Markov chains. (b) Application of Markov chains to queueing theory. (c) Poisson and renewal processes.
課程大綱 Outline of Lectures	Introduction, Random Variables Probability Distributions & Expectation Markov Chains Markov Chains Poisson Processes Poisson Processes Continuous-Time Markov Chains Midterm Exam Continuous-Time Markov Chains Renewal Processes Renewal Processes Queueing Theory Queueing Theory Queueing Network Queueing Network Final Exam"
教科書 Textbook	Ross, S.M. Introduction to Probability Models, 13th edition, Academic Press, 2023.
參考書目 References	Ross, S. M. A First Course in Probability, 7th edition, Prentice Hall, 2005. Bertsekas, D. P., Tsitsiklis, J. N., Introduction to Probability, Athena Scientific, 2002. Winston, W. L., Introduction to Probability Models－Operations Research: Volume Two, 4th Ed., Duxbury Press, 2004. Hillier, F. S., Lieberman, G. J., Introduction to Operations Research, 8th Ed., McGraw-Hill, 2005. Karlin, S., Taylor, H. M., Introduction to Stochastic Modeling, 3rd Ed., Academic Press, 1998.
修課學生須知 Notice of course enrollment	You should be comfortable with basic probability theory at the level of chapters 1-3 of Ross.
評量方式 Grading	Homework 30% Midterm Exam 35% Final Exam 35%
備註說明 Note	Homework will be assigned once every two weeks. You are encouraged to discuss homework and learn from each other, but each person must submit his/her own work.