DIGITAL SIGNAL PROCESSING LABORATORY

Prerequisites & course information

Requisites: E C E 330 and COMP SCI 300 , graduate/professional standing, or member of Engineering Guest Students Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Take specifications for a signal processing system and select an appropriate type of digital filter meeting required behavior Audience: Both Grad & Undergrad 2. Apply discrete-time linear-system theory to design a filter Audience: Both Grad & Undergrad 3. Code the filter in an algorithmic computer programming language using paradigms that allow embedding in a large software system Audience: Both Grad & Undergrad 4. Apply the theory of time-domain and Fourier-domain representations of signals and linear systems operating on those signals to interpret and verify the behavior of the coded filter Audience: Both Grad & Undergrad 5. Effectively communicate these steps in written documents Audience: Both Grad & Undergrad 6. Quantify the relative performance of digital filters in different computing environments Audience: Graduate Learning Outcomes: 1. Take specifications for a signal processing system and select an appropriate type of digital filter meeting required behavior Audience: Both Grad & Undergrad 2. Apply discrete-time linear-system theory to design a filter Audience: Both Grad & Undergrad 3. Code the filter in an algorithmic computer programming language using paradigms that allow embedding in a large software system Audience: Both Grad & Undergrad 4. Apply the theory of time-domain and Fourier-domain representations of signals and linear systems operating on those signals to interpret and verify the behavior of the coded filter Audience: Both Grad & Undergrad 5. Effectively communicate these steps in written documents Audience: Both Grad & Undergrad 6. Quantify the relative performance of digital filters in different computing environments Audience: Graduate