課程資訊
課程名稱
偵測與評估
Detection and Estimation Theory 
開課學期
103-2 
授課對象
電機資訊學院  生醫電子與資訊學研究所  
授課教師
李枝宏 
課號
EE5040 
課程識別碼
921 U1820 
班次
 
學分
全/半年
半年 
必/選修
選修 
上課時間
星期二6,7,8(13:20~16:20) 
上課地點
電二145 
備註
總人數上限:40人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1032EE5040_921U1820 
課程簡介影片
 
核心能力關聯
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課程大綱
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課程概述

DETECTION & ESTIMATION provides the mathematical background in studying Detection Theory and Estimation Theory. The Detection Theory is an engineering term for what the statistician calls Hypothesis Testing or Decision Making. The problem is one of taking measurements and then estimating in which of a finite number of states an underlying systems resides. It is used to select the physical or mathematical model from a finite class of models, that best describes measured phenomena. The Estimation Theory is an engineering term for what the statistician calls Parameter Estimation or Point Estimation. The problem is one of taking measurements and estimating the numerical value of a real or complex vector that describes the system under study. It is used to identify unknown, information-bearing parameters in a physical or mathematical model. In this course, we will discuss the following related topics:
1. Elements of Hypothesis Testing – Bayesian, Minimax, Neyman-Pearson and Composite Testings.
2. Signal Detection in Discrete Time – Models and Detector Structures, Performance Evaluation of Signal Detection Procedures, Sequential Detection.
3. Elements of Parameter Estimation – Bayesian Parameter Estimation, Nonrandom Parameter Estimation, Maximum-Likelihood Estimation.
4. Elements of Signal Estimation – Kalman-Bucy Filtering, Linear Estimation, Wiener Filtering.
5. Signal Detection in Continuous Time – The Detection of Deterministic Signals in Gaussian Noise, The Detection of Random Signals in Gaussian Noise.
6. Signal Estimation in Continuous Time – Estimation of Signal Parameters, Linear Estimation. 

課程目標
The Detection Theory is an engineering term for what the statistician calls Hypothesis Testing or Decision Making. The problem is one of taking measurements and then estimating in which of a finite number of states an underlying systems resides. It is used to select the physical or mathematical model from a finite class of models, that best describes measured phenomena. The Estimation Theory is an engineering term for what the statistician calls Parameter Estimation or Point Estimation. The problem is one of taking measurements and estimating the numerical value of a real or complex vector that describes the system under study. It is used to identify unknown, information-bearing parameters in a physical or mathematical model. 
課程要求
必須預修課程: 機率與統計, 信號與系統, 隨機信號與系統.

期中考: 45%
期末考: 45%
平日作業: 10% 
預期每週課後學習時數
 
Office Hours
 
參考書目
教科書: DETECTION, ESTIMATION, and MUDULATION THEORY, Part I. By H.L. Van Trees.

 
指定閱讀
待補 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題