Introduction to MATLAB Programming with Applications

Time: 1330 ~ 1715, Monday to Thursday
Location: Room 223B of CSIE Building (德田館)

``All science is dominated by the idea of approximation.''
-- Bertrand Russell (1872-1970)

Course Description

This course is designed for the students who want to learn MATLAB programming without any experiences before. The students are expected to be capable to implement programs with MATLAB independently after 30 hours of lectures. Furthermore, I expect you to learn other programming languages without pains in the future.

Have fun programming.

Textbook
- MATLAB: An Introduction with Applications, R. V. Dukkipati, 2010
References
- MATLAB
  - Matlab: A Practical Introduction to Programming and Problem Solving, Stormy Attaway, 3/e, 2013
  - Introduction to MATLAB for Engineers, W. J. Palm III, 3/e, 2011
  - MATLAB for Engineers, Holly Moore, 3/e, 2011
  - MATLAB Programming (online resource)
  - MATLAB程式設計《入門篇》 (online resource)
- Linear Algebra
  - Linear Algebra, Stephen H. Friedberg, Arnold J. Insel, and Lawrence E. Spence, 4/e, 2002
  - Matrix Computations, Gene H. Golub and Charles F. van Van Loan, 3/e, 1996
- Data Structures and Algorithms
  - Data Structures and Algorithms in C++, Michael T. Goodrich, Roberto Tamassia, and David M. Mount, 2/e, 2011
  - Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein, 3/e, 2009
  - Algorithms, Sanjoy Dasgupta, Christos Papadimitriou, Umesh Vazirani, 2006
  - 演算法筆記 (online resource)
- Computer Architecture
  - Computer Systems: A Programmer's Perspective, Randal E. Bryant and David R. O'Hallaron, 2/e, 2010
- Numerical Methods and Analysis
- Statistics
  - Statistical Inference, G. Casella and R. L. Berger, 2/e, 2001
  - Mathematical Statistics and Data Analysis, John A. Rice, 3/e, 2006
  - Learning From Data: An Introduction To Statistical Reasoning, Arthur Glenberg and Matthew Andrzejewski, 3/e, 2007
  - Fundamentals of Biostatistics, Bernard Rosner, 7/e, 2010
- Monte Carlo Simulation
  - Monte Carlo Methods in Financial Engineering, Paul Glasserman, 2003
- Time Series Analysis
  - Analysis of Financial Time Series, Ruey S. Tsay, 2010
- Option Pricing
  - Financial Engineering and Computation: Principles, Mathematics, Algorithms, Yuh-Dauh Lyuu, 2001
- Useful Links:
  - 為什麼要學各種程式語言, NiwaSho Lin, 2012.11.21
  - 如何成為一個偉大的開發者？, TechOrange, 2014.6.20
  - 前蘋果高層史丹佛畢典演講：想換工作，別在辦公室等著別人幫你下決定, TechOrange, 2014.7.7
  - 沒神奇公式和捷徑，這11步驟就是成為頂尖Coder的必備條件, TechOrange, 2014.7.9
  - 高生產力工程師的兩個特徵：聰明、懶惰, INSIDE, 2014.7.14

MATLAB environments
Variables and data types
Data structures: arrays, matrices, cell arrays, structure arrays
Control structures: if-elseif-else, for loop, while loop, switch-case, try-catch
Matrix computation and vectorization
2D and 3D plotting
Built-in and user-defined functions
User-controlled input and output
Graphic user interfaces
(Optional) Optimization
(Optional) Statistics and Monte Carlo simulation
(Optional) Option pricing
(Optional) Singular value decomposition (SVD) and principal component analysis (PCA)
(Optional) Numerical method of Calculus
(Optional) Time series analysis

Lecture Notes [ 236, 237, 238, 242 ]

Grading Policy

Participation (16 points)
Programming Assignment (24 points)
Final Exam (60 points)

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