課程資訊
 課程名稱 隨機訊號分析Random Signal Analysis 開課學期 104-2 授課對象 共同教育中心  統計碩士學位學程 授課教師 周呈霙 課號 BME7402 課程識別碼 631 M3140 班次 學分 3 全/半年 半年 必/選修 選修 上課時間 星期一7,8,9(14:20~17:20) 上課地點 知203 備註 本課程為學程乙組(工程環境組)選修課程之一。總人數上限：30人 Ceiba 課程網頁 http://ceiba.ntu.edu.tw/1042BME7402_random 課程簡介影片 核心能力關聯 核心能力與課程規劃關聯圖 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 Course objectives: To become familiar with the theory of random sequences and stochastic processes. To learn the mathematical tools available for the analysis and estimation of random phenomena. To see how stochastic modeling is used in practice. 課程目標 1. Review of basic probability: probability spaces, sample description spaces, events, probability measure, random variable, PDFs, PMFs, and pdfs, function of one, two, N random variables, expectations and moments, correlation coefficient, characteristic functions. 2. Random sequences: The meaning of a random sequence, stationary sequences, auto- and cross-correlation functions. Wide-sense stationary sequences; Power spectral density (psd); The Wiener – Khinchin Theorem. 3. Continuous-time random processes: The meaning of a random process; sample functions and sequences of random variables; the random telegraph signal; the binary switching sequence; the Markov random process; white noise; the independent-increment process; power spectrum and correlation functions; Input/output computations; power-spectral estimation. 4. Signal processing: The orthogonality principle; optimum interpolation; hidden Markov process; applications to speech processing; Wiener and Kalman filter. 課程要求 預修科目：工數、信號處理 預期每週課後學習時數 Office Hours 指定閱讀 待補 參考書目 Athanasios Papoulis, S. Unnikrishna Pillai, Probability, random variables, and stochastic processes, 4th Edition, McGraw-Hill, c2002. H. Stark and J. W. Woods, Probability and Random Processes with Applications to Signal Processing 3rd Edition, Prentice-Hall, 2002. 評量方式(僅供參考)
 課程進度
 週次 日期 單元主題 第1週 2/22 Introduction 第2週 2/29 No class 第3週 3/07 Random variables and probability theory 第4週 3/14 Function of a random variable 第5週 3/21 Functions of two random variables 第6週 3/28 Expected values and characteristic functions 第7週 4/04 Spring break -- no class 第8週 4/11 Two random functions of two random variables 第9週 4/18 Random vectors and processes 第10週 4/25 Midterm exam 第11週 5/02 Stochastic process 第12週 5/09 Power spectral density 第13週 5/16 White noise and match filter 第14週 5/23 Estimation theory 第15週 5/30 MAP and Mean square estimation 第16週 6/06 Decision theory 第17週 6/13 Decision theory and practice