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課程名稱 |
隨機信號和系統
STOCHASTIC SIGNALS AND SYSTEMS |
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開課學期 |
95-2 |
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授課對象 |
電機資訊學院 生醫電子與資訊學研究所 |
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授課教師 |
李枝宏 |
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課號 |
EE5024 |
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課程識別碼 |
921 U1050 |
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班次 |
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學分 |
3 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期三6,7,8(13:20~16:20) |
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上課地點 |
電二146 |
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備註 |
總人數上限：40人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/952sss_lab_jhlee_ntu |
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課程簡介影片 |
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核心能力關聯 |
本課程尚未建立核心能力關連 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
I. Probability and Random
Variables
(a) Basic Theory
(b) Transformations and
Operations on Random
Variables.
(c) Vector Random
Variables and Sequence of
Random Variables.
(d) Minimum Mean-Square
Estimation, the
Orthogonality Principles.
(e) The Multivariate
Distribution.
II. Random Processes and
Spectral Analysis
(a) Stationary
Concepts, Correlation
Functions.
(b) Time Averages,
Ergodicity.
(c) Correlation
Functions and Power Spectrum
of Stationary Random
Processes.
(d) Some Important
Random Processes.
III. Transformations and
Operations on Random
Processes.
(a) Linear Systems with
Random Inputs.
(b) Representation and
Processing of
Band-Limited Random
Processes.
(c) Finite-State Linear
Systems Driven by White
Noise.
IV. Optimum Linear Systems.
(a) Formulation of
Optimum Linear Systems.
(b) Optimum Linear
Systems that Maximize
Signal-to-Noise Ratio (SNR).
(c) The Orthogonality
Principles in Linear
Mean-Square Estimation.
(d) Least Mean-Square
Error Filtering,
Estimation, Prediction, and
the Wiener Filter Theory.
(e) Basic Principle of
Kalman Filtering. |
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課程目標 |
I. Probability and Random
Variables
(a) Basic Theory
(b) Transformations and
Operations on Random
Variables.
(c) Vector Random
Variables and Sequence of
Random Variables.
(d) Minimum Mean-Square
Estimation, the
Orthogonality Principles.
(e) The Multivariate
Distribution.
II. Random Processes and
Spectral Analysis
(a) Stationary
Concepts, Correlation
Functions.
(b) Time Averages,
Ergodicity.
(c) Correlation
Functions and Power Spectrum
of Stationary Random
Processes.
(d) Some Important
Random Processes.
III. Transformations and
Operations on Random
Processes.
(a) Linear Systems with
Random Inputs.
(b) Representation and
Processing of
Band-Limited Random
Processes.
(c) Finite-State Linear
Systems Driven by White
Noise.
IV. Optimum Linear Systems.
(a) Formulation of
Optimum Linear Systems.
(b) Optimum Linear
Systems that Maximize
Signal-to-Noise Ratio (SNR).
(c) The Orthogonality
Principles in Linear
Mean-Square Estimation.
(d) Least Mean-Square
Error Filtering,
Estimation, Prediction, and
the Wiener Filter Theory.
(e) Basic Principle of
Kalman Filtering. |
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課程要求 |
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預期每週課後學習時數 |
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Office Hours |
另約時間 |
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指定閱讀 |
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參考書目 |
(1) Saeed Ghahranani, Fundamentals of Probability, 3rd
Edition
Prentice-Hall, 2005.
(2) H. Stark and J. W. Woods, Probability and Random
Processes with Applications to Signal Processing, 3rd
Edition
Prentice-Hall, 2002. |
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評量方式
(僅供參考) |
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