syllabus

Bulletin Text:
An introduction to Scientific Computing using Matlab/Octave covering the fundamental programming concepts (data types, abstraction, control structures, I/O, modules) and demonstrating the use of Matlab/Octave to solve scientific computing problems from a variety of disciplines including physics, chemistry, biology, computer science, and math. Topics to be covered include plotting, curve fitting, image processing, optimization, integration, differentiation, statistical analysis, ODE solving, and simulation.

Textbooks:
  • MATLAB: An Introduction with Applications by Amos Gilat 3rd edition ISBN 978-0-470-10877-2  http://www.wiley.com/college/gilat or by it through Amazon for around $60
  • online octave tutorial http://www.gnu.org/software/octave/doc/interpreter/

Prerequisites: none

Course Requirements:
• Weekly homework assignments:    Students will complete weekly homework assignments to demonstrate their understanding of the concepts presented that week.
• Final Project: Students will complete a final project in which they demonstrate how matlab/octave can be used to solve a substantial scientific computing problem. They will write up their results using LaTeX, provide the matlab/octave code, and give a presentation in class with a Q&A period.

Grading:
Homework: 30%
Final Project: 40%
Final Exam and Quizzes: 30%

Tentative Course Schedule:
  • Week 1: Overview, Matlab expression syntax, Matrix and Vector syntax, ...
  • Week 2: Plotting Scatterplots, 2D and 3D graphics, image handling
  • Week 3: Function files and Script files
  • Week 4: Loops, loop-invariants, control flow, vector-operations as loops
  • Week 5: Curve fitting
  • Week 6: Modeling and simulation by difference equations
  • Week 7: Midterm review, exam, and solutions 
  • Week 8: Statistics in Matlab/Octave
  • Week 9: Ordinary Differential Equations (initial-value ODE problems) 
  • Week 10: Optimization (Linear programming, non-linear) 
  • Week 11: SVD and Principal Component Analysis 
  • Week 12: Partial Differential Equations
  • Week 13: Image processing

The concepts in weeks 8-13 will be demonstrated using examples from a variety of disciplines. For example, n-body problems, chemical dynamics, and neuron models for ODE solving, inverse kinematic robotics problems for non-linear optimization, feature analysis for image processing, public key cryptography for exact arithmetic. Topics will vary year-to-year depending on instructor.
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