本課程目標在於使學生了解機率的相關理論及其應用, 並提供學習者未來修習其他電機課程之理論基礎. 課程內容包含
(1) The axioms of probability
(2) Discrete random variable: PMF
(3) Continuous random variable: CDF and PDF
(4) Vector random variables: joint PMF, CDF, and PDF
(5) Sum of random variables主要教科書：
Alberto Leon-Garica, Probability and Random Processes for Electrical Engineering, 3rd ed. Addison-Wesley. (全華圖書)1st week: syllabus, Introduction to probability (Chapter 1)
2nd week: Probability axioms, sample space, event, permutation, (Chapter 2)
3rd week: Conditional probability, independent events, total probability, Bayes’rule
4th week: Discrete random variable (RV) and PMF (Chapter 3)
5th week: Expected and Variance of RV, conditional PMF (HW #1, due)
6th week: Some important discrete random variable
7th week: Continuous RV, CDF, and PDF (Chapter 4, HW #2, due)
8th week: Some important RV, Gaussian RV (HW #3, due)
9th week: 11/6期中考 (Chapter 2, 3, and 4)
10th week: Function of a random variable
11th week: Markov and Chebyshev inequality, and transform method
12th week: Two random variables and joint CDF and PDF (Chapter 5, HW #4, due),
13th week: Conditional CDF and PDF, independence
14th week: Functions of two RVs, Gaussian RVs (HW #5, due)
15th week: Vector random variables (Chapter 6)
16th week: Functions of RV, jointly Gaussian (HW #6, due)
17th week: no class on 1/1
18th week: 01/8期末考 (Chapter 4, 5, 6)
