EE 221: Numerical Computing for Engineers

Course Information
Course Number: 
221
Course materials
Textbook(s) (title, author, year): 

Textbook: Numerical Methods with Matlab, Gerald Recktenwald, Prentice Hall, 2000, ISBN 0201-30860-6. References:

  • Moler, Cleve B., Numerical Computing with Matlab, 2004, SIAM, Philadelphia, PA. http://www.mathworks.com/moler/
  • Applied Numerical Methods with Matlab, Steven C. Chapra, 2005, McGraw-Hill, NY.
  • Numerical Methods for Engineers, fifth ed., Steven C. Chapra and Raymond P. Canale, 2006, McGraw-Hill, NY.
  • Applied Numerical Methods for Engineers, Robert J. Schilling and Sandra L. Harris, 2000, Brooks/Cole, Pacific Grove, CA.
  • Matlab Programming for Engineers, Steven J. Chapman 2002, Brooks/Cole, Pacific Grove, CA.
  • Mastering Matlab 7, Duane Hanselman, and Bruce Littlefield, 2005, Prentice-Hall, Upper Saddle River, NJ.
  • Matlab Guide, Desmond J. Highham and Nicholas J. Higham, second ed., 2005, SIAM, Philadelphia, PA.
  • Octave Manual, http://www.octave.org/docs.html
Course Description: 
Catalog Description: 

Solutions to engineering problems making extensive use of modern software tools such as Matlab.

Specific Course Information
Topic Prerequisites: 

catalog[Math:220], catalog[Math:172] Linear algebra, calculus II and complex numbers

Overview and Course Goals
Overview and Course Goals: 

Ensure that students:

  • Can competently use the Matlab (and/or open-source alternatives such as Octave and Scilab) programming environment.
  • Understand the vector-matrix paradigm underlying Matlab (and Octave and Scilab).
  • Understand the consequences of finite precision on numeric computational and understand the inherent limits of many numerical methods.
  • Can translate a textual or mathematical descriptions of a solution into a well-written computer based solution using Matlab (or Octave or Scilab).
  • Can choose between various numerical methods to use the right method for a particular problem.
  • Understand the mathematical concepts upon which numerical methods rely.
Course Topics
Topics [with corresponding ABET outcomes]: 
  • Introduction to Matlab (Octave/Scilab) (5)
    • Running interactively
    • Syntax (including colon notation), vectors, matrices
    • Mathematical operations, built-in commands
    • Complex numbers, strings
    • Plotting
  • Programming (5)
    • m-files
    • Flow control, relational operators
    • Scope
    • Variable number of function arguments
    • Style, comments, organization
    • Debugging
  • Finite precision, inherent algorithmic errors (3)
  • Root-finding (3)
  • Solving systems of equations (5)
    • Review of linear algebra and related operations
    • Gaussian elimination
  • Least-squares fitting (3)
  • Numerical integration (4)
Course Rules
Course Rules: 
  • Homework 20%
    • Thirteen to fourteen assignments typically involving both programming and a “handwritten” component. Equal weight. No late work accepted. Lowest score dropped.
  • Tests 80%
    • Two in-class midterms, each worth 25%, and a final worth 30%. The final will be comprehensive.

Typically two 50-minute lectures per week. No labs.

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