● 課程說明(Course Desc<x>ription)
<br>數學建模之教學目標是希望學生能熟諳數據分析基本知識及技巧、具備用數學語言描述自然
<br>現象或生活中的問題，並使用數學工具解決所提出之問題。
<br>
<br>● 指定用書(Text Books)
<br>Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & 
<br>Big 
<br>Data
<br>Oxford University Press
<br>J. Nathan Kutz
<br>
<br>● 參考書籍(References)
<br>1. Data-Driven Modeling & Scientific Computation: Methods for Complex Systems 
<br>& 
<br>Big  Data
<br>Oxford University Press
<br>J. Nathan Kutz
<br>
<br>2. Mathematics and Technology 
<br>(Springer Undergraduate Texts in Mathematics and 
<br>Technology) 2008th Edition
<br>
<br>Christiane Rousseau and Yvan Saint-Aubin 
<br>
<br>https://li<x>nk.springer.com/book/10.1007/978-0-387-69216-6
<br>
<br>3. It's a Nonlinear World
<br> (Springer Undergraduate Texts in Mathematics and 
<br>Technology) 2008th Edition
<br>
<br>Richard H. Enns
<br>
<br>https://li<x>nk.springer.com/book/10.1007%2F978-0-387-75340-9
<br>
<br>4.
<br>The Mathematics of Medical Imaging
<br>A Beginner’s Guide
<br> (Springer Undergraduate Texts in Mathematics and 
<br>Technology)
<br>
<br>Timothy G. Feeman
<br>
<br>https://li<x>nk.springer.com/book/10.1007%2F978-3-319-22665-1
<br>
<br>5.
<br>Linear Algebra, Signal Processing, and Wavelets - A Unified Approach
<br> (Springer Undergraduate Texts in Mathematics and 
<br>Technology)
<br>
<br>Ryan, &#216;yvind
<br>
<br>● 教學方式(Teaching Method)
<br>板書、上機實習、學生報告
<br>
<br>
<br>● 教學進度(Syllabus)
<br>Numerical software
<br>
<br>Numerical method
<br>
<br>Classical models
<br>
<br>Possible Student project
<br>1. How does Google work?
<br>2. Linear algebra, signal processing, and wavelets.
<br>3. Functional Biomarker Analysis.
<br>4. Neuroscience and Hodgkin-Huxley model.
<br>5. Dynamic activity of earthquake in southwestern region of Taiwan
<br>6. It is a nonlinear world
<br>7. How to compute \pi?
<br>8. Otherwise.
<br>
<br>● 成績考核(Evaluation)
<br>筆試：25%
<br>上機實習及上課出席: 25%
<br>project及報告: 50%