課程資訊
課程名稱
 隨機程序及應用
Stochastic Processes and Applications 
開課學期
 109-1 
授課對象
 電機資訊學院  電機工程學研究所  
授課教師
 鐘嘉德 
課號
 EE5041 
課程識別碼
 921EU1890 
班次
  
學分
 3.0 
全/半年
 半年 
必/選修
 選修 
上課時間
 星期五7,8,9(14:20~17:20) 
上課地點
 博理114 
備註
 本課程以英語授課。
總人數上限：50人 
Ceiba 課程網頁
 http://ceiba.ntu.edu.tw/1091EE5041_SPA 
課程簡介影片
 
核心能力關聯
 本課程尚未建立核心能力關連
課程大綱
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課程概述

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. Gaussian Random Vectors and Gaussian Random Processes (Larson & Shubert, class note)
4. Signal Representation -- Karhunen-Love Expansion (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) 

課程目標
 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. 
課程要求
 Prerequisite: Probability and Statistics.
Grading Policy: There are two midterm exams and one final exam. The grading policy is "Midterm 1: 30%; Midterm 2: 30%; Final: 40%". 
預期每週課後學習時數
  
Office Hours
 另約時間 備註： 1:00pm-2:00pm, every Friday 
指定閱讀
 A. Papoulis and S.U. Pillai, Probability, Random Variables, and Stochastic Processes, fourth edition, McGraw-Hill, 2002. 
參考書目
 Textbook： There is no textbook. The course consists of lectures organized in class notes.
Reference： The class notes are organized from the content of the following references:

1. A. Papoulis and S.U. Pillai, Probability, Random Variables, and Stochastic Processes, fourth edition, McGraw-Hill, 2002.
2. H. Larson and B. Shubert, Probabilistic Models in Engineering Sciences, vols. 1 and 2, Wiley, 1979.
3. W. Davenport and W. Root, An Introduction to the Theory of Random Signals and Noise, McGraw Hill, 1958.
4. L. Sharf, Statistical Signal Processing: Detection, Estimation, and Time Series Analysis, Addison-Wesley, 1990.
5. E. Wong and B. Hajek, Stochastic Processes in Engineering Systems, Springer-Verlag, 1985.
6. A. Leon-Garcia, Probability and Random Processes for Electrical Engineering, Addison-Wesley, 1989. 
評量方式
(僅供參考)
    
課程進度
週次
日期
單元主題
第1週
 9/18  Review of Random Variables 
第2週
 9/25  Review of Random Variables 
第3週
 10/02  Introduction to Random Processes: General Concepts and Spectral Analysis 
第4週
 10/09  Introduction to Random Processes: General Concepts and Spectral Analysis 
第5週
 10/16  Introduction to Random Processes: General Concepts and Spectral Analysis 
第6週
 10/23  First Midterm + Gaussian Random Vectors and Gaussian Random Processes 
第7週
 10/30  Gaussian Random Vectors and Gaussian Random Processes 
第8週
 11/06  Gaussian Random Vectors and Gaussian Random Processes 
第9週
 11/13  Signal Representation -- Karhunen-Love Expansion 
第10週
 11/20  Narrowband Processes and Bandpass System 
第11週
 11/27  Narrowband Processes and Bandpass System 
第12週
 12/04  Second Midterm + Poisson Processes 
第13週
 12/11  Poisson Processes 
第14週
 12/18  Markov Processes and Markov Chains 
第15週
 12/25  Markov Processes and Markov Chains 
第16週
 1/01  Queuing Systems 
第17週
 1/08  Random Walk Processes and Brownian Motion Processes