Download 國立台灣大學電機學院開授課程大綱格式

國立台灣大學電資學院電機學群開授課程大綱格式
所別:
組別:
修習年級: 3、4、碩士班、博士班
V 1.一般性課程 (含必修、選修)
課
2.通識教育課程【
每週演講時數:
3
】(1)人文(2)社會(3)物質(4)生命
程
3.教育學程
4.軍訓課程
課號: 921 U1890
中文名稱:
授課教師
課程大綱
班次:
隨機程序及應用
學分: 3
英文名稱: STOCHASTIC PROCESSES AND APPLICATIONS
鐘嘉德
Instructor:
Char-Dir Chung
Office: Barry Lam Hall, Room 426
Tel: (02) 33663596
E-mail: [email protected]
Description:
The purpose of this course is to provide students with a solid and pertinent mathematical
background for thoroughly understanding digital communications and communication networks.
It is a prerequisite for advanced study of numerous communication applications, including
wireless communications, mobile communications, communication networks, spread spectrum
communications, satellite communications, optical communications, radar and sonar signal
processing, signal synchronization, etc. The students majoring in communications and networks
are strongly recommended to take this course. The course consists of lectures organized in class
notes.
(請以英文書
寫)
一.內容
5.體育課程
二.教科書
三. 成績評
量方式
四. 預修課程
(每行 30 個中 Lecture Time:
文字,全文限
Class Website:
800 個中文
2:20pm-5:10pm, Friday
http://homepage.ntu.edu.tw/~r03942062/spa1041.htm
字,即 1600 個 Prerequisites:
Probability and Statistics
英文字)
A. Papoulis and S.U. Pillai, Probability, Random Variables, and Stochastic Processes, fourth
edition, McGraw-Hill, 2002.
H. Larson and B. Shubert, Probabilistic Models in Engineering Sciences, vols. 1 and 2, Wiley,
1979.
W. Davenport and W. Root, An Introduction to the Theory of Random Signals and Noise,
McGraw Hill, 1958.
L. Sharf, Statistical Signal Processing: Detection, Estimation, and Time Series Analysis,
Addison-Wesley, 1990.
E. Wong and B. Hajek, Stochastic Processes in Engineering Systems, Springer-Verlag, 1985.
A. Leon-Garcia, Probability and Random Processes for Electrical Engineering, Addison-Wesley,
1989.
1. Review of Random Variables (Papoulis, Chaps. 1-7, and class note)
2. Introduction to Random Processes: General Concepts and Spectral Analysis (Papoulis, Chap.
9, and class note)
3. Real-Valued Gaussian Random Vectors and Real-Valued Gaussian Random Processes (Larson
& Shubert, class note)
4. Karhunen-Love Representation (Papoulis, Chap. 11, and class note)
5. Narrowband Processes and Bandpass Systems (Davenport and Root, and class note)
6. Poisson Processes (Larson & Shubert, Leon-Garcia, and class note)
7. Markov Processes and Markov Chains (Larson & Shubert, Leon-Garcia, and class note)
8. Queuing Systems (Leon-Garcia)
9. Random Walk Processes and Brownian Motion Processes (Leon-Garcia)
Reference Books:
Course Outline:
Homeworks:
There will be six homeworks, one every three weeks.
Midterm/Final:
There will be one midterm and one final exam during the university-scheduled midterm and final
exam weeks.
Grading:
Homework: 30%; Midterm: 35%; Final: 35%
更新日期
105
年
8
月
1
日