|
課程名稱 |
偵測與評估
DETECTION AND ESTIMATION THEORY |
|
開課學期 |
96-2 |
|
授課對象 |
電機資訊學院 電機工程學研究所 |
|
授課教師 |
李枝宏 |
|
課號 |
EE5040 |
|
課程識別碼 |
921 U1820 |
|
班次 |
|
|
學分 |
3 |
|
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：30人 |
|
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/962921U1820_2008 |
|
課程簡介影片 |
|
|
核心能力關聯 |
本課程尚未建立核心能力關連 |
|
課程大綱
|
|
為確保您我的權利,請尊重智慧財產權及不得非法影印
|
|
課程概述 |
CONTENTS:
I. Elements of Hypothesis Testing:
(a) Bayesian Detection Criterion.
(b) Minimum Probability of Error Detection Criterion.
(c) Minimax Detection Criterion.
(d) Maximum Likelihood (ML) Detection Criterion.
(e) Neyman-Pearson Detection Criterion.
(f) Composite Hypotheses Testing.
II. Signal Detection in Discrete Time:
(a) Models and Detector Structures.
(b) Performance Evaluation of Signal Detection Procedures.
III. Elements of Parameter Estimation:
(a) Estimation of Random Parameters − Bayesian Estimation Criterion, Maximum A Posteriori (MAP) Estimation Criterion.
(b) Estimation of Non-Random Parameters − Maximum Likehood (ML) Estimation Criterion.
(c) Multiple Parameter Estimation:
(1) Bayesian Estimation Criterion.
(2) MAP Estimation Criterion.
(3) ML Estimation Criterion.
IV. Representation of Random Signals:
(a) Orthogonal Representations for Deterministic Functions.
(b) Karhunen-Loeve Representation for Random Signals (KL Expansion).
IV. Detection of Signals in Continuous Time:
(a) The Detection of Signals in Aditive White Gaussian Noise (AWGN).
(b) The Detection of Signals in Aditive NonWhite Gaussian Noise.
V. Estimation of Signals in Continuous Time:
(a) The Estimation of Signals in Aditive White Gaussian Noise (AWGN).
(b) The Estimation of Signals in Aditive NonWhite Gaussian Noise.
VI. Optimum Linear Systems for Estimation:
(a) Innovation Sequences.
(b) Estimation, Prediction, and the Kalman Filter Theory.
|
|
課程目標 |
CONTENTS:
I. Elements of Hypothesis Testing:
(a) Bayesian Detection Criterion.
(b) Minimum Probability of Error Detection Criterion.
(c) Minimax Detection Criterion.
(d) Maximum Likelihood (ML) Detection Criterion.
(e) Neyman-Pearson Detection Criterion.
(f) Composite Hypotheses Testing.
II. Signal Detection in Discrete Time:
(a) Models and Detector Structures.
(b) Performance Evaluation of Signal Detection Procedures.
III. Elements of Parameter Estimation:
(a) Estimation of Random Parameters − Bayesian Estimation Criterion, Maximum A Posteriori (MAP) Estimation Criterion.
(b) Estimation of Non-Random Parameters − Maximum Likehood (ML) Estimation Criterion.
(c) Multiple Parameter Estimation:
(1) Bayesian Estimation Criterion.
(2) MAP Estimation Criterion.
(3) ML Estimation Criterion.
IV. Representation of Random Signals:
(a) Orthogonal Representations for Deterministic Functions.
(b) Karhunen-Loeve Representation for Random Signals (KL Expansion).
IV. Detection of Signals in Continuous Time:
(a) The Detection of Signals in Aditive White Gaussian Noise (AWGN).
(b) The Detection of Signals in Aditive NonWhite Gaussian Noise.
V. Estimation of Signals in Continuous Time:
(a) The Estimation of Signals in Aditive White Gaussian Noise (AWGN).
(b) The Estimation of Signals in Aditive NonWhite Gaussian Noise.
VI. Optimum Linear Systems for Estimation:
(a) Innovation Sequences.
(b) Estimation, Prediction, and the Kalman Filter Theory.
|
|
課程要求 |
PREREQUISITE COURSES:
Probability and Statistics, Signals and Systems, and Stochastic Signals and Systems are the requisitions for taking this course.
|
|
預期每週課後學習時數 |
|
|
Office Hours |
每週一 09:10~10:00 備註： TA Office Hour:
地點:博理館527.
若欲找我討論功課, 請事先email告知(一天以前), 我人才會在實驗室. |
|
參考書目 |
(1) D. Kazakos and P. Papantoni-Kazakos, Detection and
Estimation, Computer Science Press, 1990.
(2) H. Vincent Poor, An Introduction to Signal Detection
and Estimation, Springer-Verlag, New York, 1988.
(3) H. Stark and J. W. Woods, Probability and Random
Processes with Applications to Signal Processing, 3rd
Edition
Prentice-Hall, 2002.
|
|
指定閱讀 |
|
|
評量方式
(僅供參考) |
|
No. |
項目 |
百分比 |
說明 |
|
1. |
期中考 |
45% |
|
2. |
期末考 |
45% |
|
3. |
隨堂測驗 |
0% |
|
4. |
作業 |
10% |
|
5. |
報告 |
0% |
|
|
|