課程說明(Course Desc<x>ription):
<br>The goals for  this course are using matrices and also understanding them. Abstract concepts will be presented and  Computational algorithms will also be highlighted.
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<br>指定用書(Text Books)
<br>G. Strang, Introduction to Linear Algebra, Wellesley-Cambridge Press,  4th or 5th Ed. 
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<br>中文版
<br>http://www.books.com.tw/products/0010308475
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<br>The author's web page and the coursed Video is located at
<br>http://www-math.mit.edu/~gs/
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<br>趙啟超教授清華開放式平台
<br>http://ocw.nthu.edu.tw/ocw/index.php?page=course&cid=89
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<br>參考書籍(References)
<br>1. G. Strang, Linear Algebra and Its Applications, Brooks Cole; 4th edition, 2006.
<br>2. Stephen H. Friedberg,  Arnold J. Insel,  and  Lawrence E. Spence, Linear Algebra, 3rd Ed.  Prentice Hall,  1996. (Theorem-Proof  st<x>yle)
<br>3. Lawrence E. Spence, Arnold J. Insel,  Stephen H. Friedberg,  Elementary Linear Algebra, 2nd Edition,  Pearson, 2007.
<br>4. Serge Lang, Linear Algebra, Undergraduate Texts in Mathematics, 3rd Edition, Springer, 2004. (Theorem-Proof  st<x>yle)
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<br>教學方式(Teaching Method)
<br>Lecture + Matlab  Lab. 
<br>教學進度(Syllabus)
<br>1 Introduction to Vectors 
<br>2 Solving Linear Equations
<br>3 Vector Spaces and Subspaces 
<br>4 Orthogonality 
<br>5 Determinants
<br>6 Eigenvalues and Eigenvectors
<br>7 The Singular Value Decomposition (SVD) 
<br>8 Linear Transformations 
<br>9 Complex Vectors and Matrices 
<br>10 Applications
<br>11 Numerical Linear Algebra 
<br>12 Linear Algebra in Probability & Statistics 
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<br>成績考核(Evaluation)
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<br>6 Quizs (Each 8%)+   2 Midterms ( Each 16%) + 1 Final (20%)