Instructor:
Michael T Johnson
699
Credits:
3.0
003
Building:
Robotics & Manufacturing Building
Room:
Rm.309
Semester:
Spring 2025
Start Date:
End Date:
Name:
Tops In Ee: Digital Signal Processing
Requisites:
Prereq: Consent of instructor.
Class Type:
LEC
9:30 am
10:45 am
Days:
TR
Note:
This course is an introduction to the theory and practice of discrete- time signals and systems, an important topic essential to the design and understanding of modern audio and video processing and communications systems. Theoretical concepts to be covered include Fourier Transforms, Z-transforms, linear time invariant system analysis in the time and frequency domains, sampling theory, and Discrete Fourier Transforms. Application of these concepts will include digital filter design techniques and the use of Fast Fourier Transforms for efficient frequency domain analysis. In addition, the course will provide an introduction to the application of machine learning concepts to signal processing problems. Example applications and design projects related to specific signal processing tasks will be used to illustrate the material. Prereq: EE421G Signals and Systems or Equivalent. Background needed: Continuous-time linear systems, convolution, Fourier Series, Fourier Transforms,
A detailed study of a topics of current interest in electrical engineering. May be repeated to a maximum of six credits, but only three credits may be earned under the same subtitle. A particular topic may be offered at most twice under the EE 699 number.
A detailed study of a topics of current interest in electrical engineering. May be repeated to a maximum of six credits, but only three credits may be earned under the same subtitle. A particular topic may be offered at most twice under the EE 699 number.
EE