Schedule: EECE645

Quiz # Date Study Period Topic 한국어 강의 Lecture in English Exam Schedule

1 9/10 9/3 ~ 9/9 Introduction, Maximum A Posteriori Probability (MAP) detector Lec1, Lec2, Lec3 Lec1, Lec2, Lec3 　

2 9/17 9/10 ~ 9/16 General Bayesian Hypothesis Testing Lec4, Lec5, Lec6 Lec4, Lec5 　

3 10/1 9/17 ~ 9/23 Minimax Hypothesis Testing Lec7, Lec8, Lec9 Lec6 　

　　 9/24 ~ 9/30 추석 연휴 　　　

4 10/8 10/1 ~ 10/7 Neyman-Pearson Hypothesis Testing Lec10, Lec11, Lec12 Lec7, Lec8 　

5 10/15 10/8 ~ 10/14 Composite Hypothesis Testing, General Bayesian Estimators, MMAE Estimator, MAP Estimator Lec13, Lec14, Lec15 Lec9, Lec10 10/17 1st Midterm

6 10/22 10/15 ~ 10/21 MMSE Estimator, LMMSE Estimator, AMMSE Estimator, BLUE Lec16, Lec17, Lec18 Lec11, Lec12, Lec13 　

7 10/29 10/22 ~ 10/28 BLUE, Sufficient Statistic Lec19, Lec20, Lec21 Lec14, Lec15, Lec16 　

8 11/5 10/29 ~ 11/4 UMVU Estimator, Cramer-Rao Lower Bound Lec22, Lec23, Lec24 Lec17, Lec18, Lec19 　

9 11/12 11/5 ~ 11/11 MVUE, Maximum Likelihood Estimator Lec25, Lec26, Lec27 Lec20, Lec21 　

10 11/19 11/12 ~ 11/18 EM Algorithm, SRRT Lec28, Lec29, Lec30 Lec22, Lec23 　

11 11/26 11/19 ~ 11/25 Estimation of Stationary Process: Wiener Filter, Estimation of Nonstationary Process: Kalman Filter Lec31, Lec32 Lec24, Lec25, Lec26 11/22 2nd Midterm

12 12/3 11/26 ~ 12/2 MLE revisited, Sampling Theorem, Irrelevant Observation, Gram-Schmidt Orthogonalization Lec33, Lec34, Lec35 Lec27, Lec28, Lec29 　

13 12/10 12/3 ~ 12/9 Karhunen-Loeve (KL) Expansion, Whitening Lec36, Lec37, Lec38 Lec30, Korean Lec38 12/17 Final Exam

CM#1: Note, Video

Quiz #	Date	Study Period	Topic	한국어 강의	Lecture in English	Exam Schedule
1	9/10	9/3 ~ 9/9	Introduction, Maximum A Posteriori Probability (MAP) detector	Lec1, Lec2, Lec3	Lec1, Lec2, Lec3
2	9/17	9/10 ~ 9/16	General Bayesian Hypothesis Testing	Lec4, Lec5, Lec6	Lec4, Lec5
3	10/1	9/17 ~ 9/23	Minimax Hypothesis Testing	Lec7, Lec8, Lec9	Lec6
		9/24 ~ 9/30	추석 연휴
4	10/8	10/1 ~ 10/7	Neyman-Pearson Hypothesis Testing	Lec10, Lec11, Lec12	Lec7, Lec8
5	10/15	10/8 ~ 10/14	Composite Hypothesis Testing, General Bayesian Estimators, MMAE Estimator, MAP Estimator	Lec13, Lec14, Lec15	Lec9, Lec10	10/17 1st Midterm
6	10/22	10/15 ~ 10/21	MMSE Estimator, LMMSE Estimator, AMMSE Estimator, BLUE	Lec16, Lec17, Lec18	Lec11, Lec12, Lec13
7	10/29	10/22 ~ 10/28	BLUE, Sufficient Statistic	Lec19, Lec20, Lec21	Lec14, Lec15, Lec16
8	11/5	10/29 ~ 11/4	UMVU Estimator, Cramer-Rao Lower Bound	Lec22, Lec23, Lec24	Lec17, Lec18, Lec19
9	11/12	11/5 ~ 11/11	MVUE, Maximum Likelihood Estimator	Lec25, Lec26, Lec27	Lec20, Lec21
10	11/19	11/12 ~ 11/18	EM Algorithm, SRRT	Lec28, Lec29, Lec30	Lec22, Lec23
11	11/26	11/19 ~ 11/25	Estimation of Stationary Process: Wiener Filter, Estimation of Nonstationary Process: Kalman Filter	Lec31, Lec32	Lec24, Lec25, Lec26	11/22 2nd Midterm
12	12/3	11/26 ~ 12/2	MLE revisited, Sampling Theorem, Irrelevant Observation, Gram-Schmidt Orthogonalization	Lec33, Lec34, Lec35	Lec27, Lec28, Lec29
13	12/10	12/3 ~ 12/9	Karhunen-Loeve (KL) Expansion, Whitening	Lec36, Lec37, Lec38	Lec30, Korean Lec38	12/17 Final Exam