National Tsing Hua University
Department of Computer Science

Course Title: CS3331 :     Numerical Methods       CS3331 Scores 

Credits: 3 (Fall, 2009)      

Classes: 1:10-2:00, Tuesday and 1:10-3:00, Friday at EECS 131

Instructor: Chaur-Chin Chen

Tel/E-mail: (03) 573-1078 (O),     (03) 574 2809 (Lab),     cchen@cs.nthu.edu.tw

Prerequisites: C/C++ ,   Data Structure ,   Linear Algebra ,   Differential Equations ,   [Probability Theory]  

Contents:
1. Foundations    
2. Solving Linear Systems of Equations     Gaussian Elimination P.P.     G.E. with Partial Pivoting     Test data for G.E.P.P.
    C program for Crout Algorithm     Test data
3. The Linear Least Squares Problems       Polynomial Regression     dataGPA.txt     dataQua.txt     Visualization
4. Computing Eigenvalues and Eigenvectors      
    Givens Rotations for Computing Eigenvalues     Codes for Power method ;
    Drive for Power method
5. Nonlinear Equations    
    Matlab Code for Fixed Point Demo;     Result;
6. Interpolation and Approximation       Greek letters
7. FFT and DCT with Applications     DFT and DCT Examples
    Matlab Example for 2d DCT     An 8x8 block from Lenna     Quantization Table
8. Numerical Differentiation and Integration *     Matlab Program for Richardson Extrapolation Algorithm
R. Solving Problems by Using Matlab   
    Sine     Ln(x)     Solving Hx=1     Characteristic Polybomial    Finding Median of ChiSquare    Solutions for Nonlinear Eqs

Textbooks:
Laurene V. Fausett, Applied Numerical Analysis Using Matlab, 2nd edition, Pearson International Edition, Prentice Hall (2008)

References:
1. J.D. Faires and R.L Burden , Numerical Methods, Prentice-Hall (2003)
2. D. Hanselman and B. Littlefield, Mastering MatLab 7 (2005)
3. D. Kincaid and W. Cheney, Numerical Analysis, 3rd ed. Brooks/Cole (2002)
4. J.H. Mathews and K.D. Fink, Numerical Methods Using Matlab, Prentice-Hall (2004)
5. G. Recktenwald, Numerical Methods with Matlab, Prentice-Hall (2000)
6. T. Hastie, R. Tibshirani, and J. Friedman , The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2001)
7. M.T. Heath , Scientific Computing: An Introductory Survey, 2nd ed., McGraw-Hill Companies, Inc. (2002)

Grading:
  • (30%) Homework Assignments
  • (70%) Exam

    Updated on May 10, 2020