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課程名稱 |
時序資料分析
Time Series Analytics |
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開課學期 |
108-1 |
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授課對象 |
工學院 工業工程學研究所 |
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授課教師 |
藍俊宏 |
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課號 |
IE5057 |
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課程識別碼 |
546EU4050 |
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班次 |
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學分 |
3.0 |
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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 |
星期三2,3,4(9:10~12:10) |
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上課地點 |
國青101 |
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備註 |
本課程以英語授課。
總人數上限：31人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1081IE5057_ |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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課程概述 |
Time series and signals exist everywhere, and, in particular, the data collection and analysis are much easier than before with the advancement of modern information technology. This course starts by modeling the common time series, such as the demands, economic indicators. Digital signals, such as the machine sensor readings, ECG, and soundwaves are then analyzed with signal processing techniques. The goal is to develop a general sense of treating temporal signals. |
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課程目標 |
Students from this course shall learn to:
1. comprehend the characteristics of different time series and signals;
2. understand the time series identification, estimation, and diagnostic;
3. understand the analytical techniques for digital signal processing;
4. apply proper treatments for analyzing time-series data.
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課程要求 |
probability & statistics, linear algebra, calculus, and programming skills |
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
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參考書目 |
• Box, G. E. P., Jenkins, G. M., Reinsel, G. C., and Ljung, G. M. (2016). Time Series Analysis: Forecasting and Control.
• Davis, M. H. A., and Vinter, R. B. (1985). Stochastic Modelling and Control.
• Tsay, R. (2010). Analysis of Financial Time Series.
• Smith, S. W. (1999). The Scientist and Engineer's Guide to Digital Signal Processing.
• Lyons, R. G. (2010). Understanding Digital Signal Processing.
• Mallat, S. (2008). A Wavelet Tour of Signal Processing.
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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Week 1 |
9/11 |
Review of Pre-requisites and Introduction to Time-Series |
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Week 2 |
9/18 |
Exponential Smoothing Models |
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Week 3 |
9/25 |
Univariate Stationary Time Series Models |
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Week 4 |
10/02 |
Univariate Stationary Time Series Models |
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Week 5 |
10/09 |
Univariate Nonstationary Time Series Models |
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Week 6 |
10/16 |
Model Identification, Estimation, and Diagnostic |
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Week 7 |
10/23 |
Model Identification, Estimation, and Diagnostic |
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Week 8 |
10/30 |
Mid-term Exam |
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Week 9 |
11/06 |
Multivariate Time Series Models |
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Week 10 |
11/13 |
Introduction to Digital Signals |
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Week 11 |
11/20 |
Time-Frequency Analysis |
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Week 12 |
11/27 |
Time-Frequency Analysis |
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Week 13 |
12/04 |
Wavelet Transformation |
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Week 14 |
12/11 |
Wavelet Transformation |
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Week 15 |
12/18 |
Recursive Filter |
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Week 16 |
12/25 |
Recurrent Neural Network |
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Week 17 |
1/01 |
Bank Holiday |
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Week 18 |
1/08 |
Final-term Exam |
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