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ITEC 330

ITEC 330: Numerical Analysis

Prerequisite: MATH 251 and ITEC 120.

Credit Hours: (3)

A study of algorithms useful in obtaining numerical solutions of problems on a digital computer. Students who have received credit for CPSC 330 may not receive credit for ITEC 330.

 

Detailed Description of Content of Course

Topics covered:

 

1. Mathematical software design considerations
2. Rudiments of floating point arithmetic
3. Systems of linear equations
4. Interpolation and data fitting
5. Integration and quadrature
6. Linear least squares and regression
7. Nonlinear equations

 

If time permits some instructors may include additional topics from the following list:

 

8. Ordinary differential equations
9. Nonlinear optimization
10. Nonlinear least squares and regression
11. Trigonometric approximation and Fourier analysis
12. Random number generation
13. Specialized software systems (e.g., MATLAB, MATHEMATICA)
14. Linear programming

 

Detailed Description of Conduct of Course

Coursed material is presented via lecture and class discussion. This course emphasizes problem solving through the use of techniques and software appropriate for scientific computing. Some instructors may require students to work together in small groups. In all sections students will be asked to work problems assigned as homework. Some of the assignments will require students to use the computer.

 

Goals and Objectives of the Course

1. The student is expected to develop an understanding of the methods available for solving scientific computing problems.
2. The student is expected to acquire familiarity and experience with selected high-quality mathematical software for scientific computing.
3. The student is expected to develop an ability to attack and successfully solve scientific computing problems.

 

Assessment Measures

Graded tasks may include tests, quizzes, homework exercise, programs, class participation, and attendance.

 

Other Course Information

This class is offered for undergraduate students in computer science, mathematics, and statistics, and other fields in which scientific computing problems arise.

 

Review and Approval


September 2001 Updated John P. Helm, Chair