Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2025	350366	Random Signals and Systems	1	3.0	3	★	HO-TING WU	GCSIE IEECSG	4	0	Jointly offered by Computer Science department.

Course Plan：

Instructor	HO-TING WU　Office Hours
Email	htwu@ntut.edu.tw
Last Updated	2025-05-19 10:10:40
Course Objective	This course contains the basic theories in probability and random processes. It includes probability measures, random variables, the law of large number, statistical inference, random processes and stationary processes. This course offers substantial probabilistic and statistical backgrounds for the machine learning (ML) field and serves as a basic course in field of communications, networks and controls in graduate school.
Course Schedule	The course website is posed on course "1141_隨機信號與系統_350366" in the platform of 北科i學園PLUS platform. Please check course link (https://istudy.ntut.edu.tw/learn/index.php) for course website. Announcement, homework assignment and updated information will be posted on the course website. Week 1. Reviews of Probability Concepts Week 2. Discrete and Continuous Random Variables Week 3. Sequential Events, Conditional Probability and Conditional Expectation Week 4. Multiple Random Variables Week 5. Functions of Random Variables Week 6. Random Vectors Week 7. Sums of Random Variables Week 8. Moment Generating Functions, Central Limit Theorem Week 9. Midterm; The Sample Mean Week 10. Point Estimates of the Model Parameter Week 11. Confidence Intervals; Significance Testing Week 12. Binary and Multiple Hypothesis Testing Week 13. Estimation of Random Variables Week 14. Optimal Estimation; MAP and ML Estimation Week 15. Definitions and Types of Random Processes Week 16. The Poisson Process; The Brownian Process Week 17. Stationary Random Processes Week 18. Final Exam
Evaluation and grading policy	1. Homeworks + Class Participation 40% 2. Midterm Exam 30% 3. Final Exam. 30%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Prerequisites: Probability, Transform Theory Textbook: Yates and Goodman, “Probability and Stochastic Processes,” 2nd Ed., John Wiley & Sons, 2005. (You may choose the 3rd ed. of this textbook, which contains similar contents and was published in 2015.) References: 1. Leon-Garcia, “Probability and Random Processes for Electrical Engineering,” 3rd ed., Pearson, 2009. 2. Childers, “Probability and Random Processes”, Irwin, 1997. 3. Papoulis and Pillai, “Probability, Random Variables, and Stochastic Processes,” 4th ed., Mc-Graw-Hill, 2002. 4. Stark and Woods, “Probability and Random Processes with application to Signal Processes”, 3rd ed., Prentice Hall, 2002. 5. Ross, “Introduction to Probability Models”, 7th ed., Academic Press, 2000. 6. Ghahramani, “Fundamentals of Probability with Stochastic Processes”, 3rd ed., Prentice Hall, 2005. 7. Bhat and Miller, “Elements and Applied Stochastic Processes”, 3rd ed., 2002. 8. Ross, “A First Course in Probability”, 7th ed., Prentice -Hall, 2006
The access to curricular consultation	Welcome to check with me during the office hours or send email in advance to arrange a personal meeting schedule. Prof. Ho-Ting Wu Office location: Room# 1528, Technology Building. (O)(02)27712171 x 4221 email: htwu@ntut.edu.tw
The course corresponds to the SDGs	SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure）
Does the course incorporate AI
Note