Introduces theory and methods to characterize and process biological signals from a variety of sources and engineering applications in the time and frequency domains. This course covers mathematical and computational tools for signal analysis with emphasis on discrete time signals and digital processing. Topics include noise, sampling, Fourier transforms, filter design, LTI systems, and image processing with exercises in MATLAB. Recommended prerequisite: BMEN 3030. Degree credit not granted for this course and ECEN 3300.
instructor(s)
Bottenus, Nick
Primary Instructor
- Spring 2023 / Spring 2024
