MTH 451 Fourier Analysis and Its Applications

In this class, students will be exposed to orthogonal functions, Fourier series, Fourier transforms, and a variety of additional convolution and filtering techniques.  Students will also see applications of Fourier analysis in fields such as signal and image processing and time series analysis. Prerequisites:  (at least one of CS 130, STS 327, STS 347); MTH 251; or permission of the instructor. Offered Spring of odd years.

Credits

4

Prerequisite

Prerequisites:  (at least one of CS 130, STS 327, STS 347); MTH 251; or permission of the instructor.

Course Types

Non-lab science

Offered

• Spring

Course Outcomes

1. Learning Outcomes
   Students will
   • Have a deeper understanding of orthogonality, particularly in relation to function spaces.
   • Have a deeper understanding of the importance of series approximation of data
   • Have an understanding of the difference between time and frequency space
   • Have a deeper understanding of the importance of convolution and filtering techniques when studying data
   • Have a better appreciation of importance of Fourier analysis related to signal and image processing
   • Have an increased proficiency of mathematical computing as it is applied to Fourier analysis