檢測與估計理論

Detection and Estimation Theory

學期

106-1

學分

3 學分

當期課號

5066

永久課號

ICN9004

開課單位

電控工程研究所

授課教師

蔡尚澕

校區

光復

類別

選修

上課時間表

節	週一
5 13:20–14:10	檢測與估計理論 EE105 3 節連堂
6 14:20–15:10
7 15:30–16:20

* 根據陽明交大上課時間表所列

概述

We introduce various estimators and the corresponding estimation theory. We cover the topics including: minimum variance unbiased (MVU) estimation, Cramer-Rao Lower Bound (CRLB), linear model, sufficient statistics, best linear unbiased estimatiors, maximum likelihood estimation, least square approach, Bayesian estimators, hypothesis testing, various detectors for deterministic and random signals. Note that this time Detection Theory is covered.

先修科目

Random process, probability and linear algebra

教學方式

Lecture notes will be made available on the e3 website TAs 羅信原 q5566007789@gmail.com 何國誠 aqw173568@gmail.com 賴佳欣 emily_0736@yahoo.com.tw 何彥胤 thumbd91602@yahoo.com.tw 陳筱茜 u950873@gmail.com

評分方式

Homework: 20% (Some homework requires the use of Matlab) Midterm-I: 25% Midterm-II: 25% Final: 30%

週次計畫

週次	主題
第 1 週	1. Minimum variance unbiased estimation 2. Cramer-Rao lower bound 3. Linear models 4. General minimum variance unbiased estimation 5. BLUE 6. ML estimation 7. LS estimation 8. Bayesian estimations 9. Neyman-Pearson Theorem 10. Detection for deterministic signals

教科書

Text Book [1] Steven M. Kay, “Fundamentals of Statistical Signal Processing: Volume I Estimation Theory,” Prentice Hall 1993. [2] Steven M. Kay, “Fundamentals of Statistical Signal Processing: Volume II Detection Theory,” Prentice Hall 1998. Reference Books [1] H. Stark and J. W. Woods, Probability and Random Processes with Applications to Signal Processing, Prentice Hall, 2001 [2] A. Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Process, McGraw-Hill, New York US, 2002 [3] Gilbert Strang, Linear Algebra and Its Applications, Brooks Cole, 2005

Office Hours

地點: EE734
時間: 16:40-17:30, Thursday, or by appointment
聯絡方式: Ext. 54346 Email: shanghot@mail.nctu.edu.tw