檢測與估計
Detection and Estimation
| 節 | 週二 | 週四 |
|---|---|---|
3 10:10–11:00 | 檢測與估計 ED101 2 節連堂 | |
4 11:10–12:00 | ||
5 13:20–14:10 | 檢測與估計 ED101 |
* 根據陽明交大上課時間表所列
學習檢測理論與估測理論之基本學理 Major Topics: Estimation Part: 1. Introduction 2. Minimum Variance Unbiased Estimation 3. Cramer-Rao Lower Bound 4. Linear Models 5. General MVU Estimation 6. Baset Linear Unbiased Estimators 7. Maximum Likelihood Estimators 8. Least Squares 9. Method of Moments 10. Bayesian Estimator 11. Linear Bayesian Estimators Detection Part: 1. Introduction 2. Statistical Decision Theory I 3. Detecting Signals in Gaussian Noise 4. Statistical Decision Theory II
線性代數, 隨機過程
Classroom: You may either come to the calssroom or listen to the lectures via Google Meet. 10:10am-Noon ED201 Tuesday (Live broadcast: https://meet.google.com/fwi-kraa-mcy) 1:20pm-2:10pm ED101 Thursday (Live broadcast: https://meet.google.com/ieb-csop-dss) Handouts: Available at NYCU E3 platform
考試部份: open book, open notes 評量部份: Homework 20% Midterm Exam 35% (10:10pm – Noon, 2023/4/11) Final Exam 45% (1:20pm - 4:20pm, 2023/6/1)
| 週次 | 主題 |
|---|---|
| 第 1 週 | • Introduction • MVU Estimation Cramer-Rao Lower Bound |
| 第 2 週 | • Concept & Proof of Cramer-Rao Lower Bound • CRLB for vector parameters |
| 第 3 週 | (二二八假期) • Examples of CRLB |
| 第 4 週 | • Linear Models • Extention to the Linear Model • Sufficient Statistics |
| 第 5 週 | • General MVU Estimation • RBLS Theorem • Extension to vector parameters |
| 第 6 週 | |
| 第 7 週 | |
| 第 8 週 | (清明連假) |
| 第 9 週 | Midterm (4/11) |
| 第 10 週 | |
| 第 11 週 | |
| 第 12 週 | |
| 第 13 週 | |
| 第 14 週 | |
| 第 15 週 | |
| 第 16 週 | Final (6/1) |
| 第 17 週 | |
| 第 18 週 |
Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory by Steven M. Kay, Prentice Hall, 1993. (Optional) Fundamentals of Statistical Signal Processing, Volume II: Detection Theory (Chap 1 ~ Chap 6) by Steven M. Kay, Prentice Hall, 1993.
- 地點
- ED649
- 時間
- 2:00pm-3:00pm Wednesday
- 聯絡方式
- shengjyh@nycu.edu.tw