EE445S Real-Time Digital Signal Processing Laboratory

Prof. Brian L. Evans, The University of Texas at Austin, Fall 2018, MWF 11:00am-12:00pm, ECJ 1.308

Office Hours: MWF 10:00-11:00am EER 6.882

General information: Overview Description Textbooks Prerequisites Related courses
Course resources: Lecture Handouts Homework Laboratory Reader
Other information: Alumni Canvas LabVIEW demo Web resources Thanks
CommSys@UT: Faculty Undergrad study Graduate study Research

Download the course reader, which includes all lecture slides, all handouts, and recent midterm exams.

In the Real-Time Digital Signal Processing Laboratory course, students derive algorithms from signal processing theory and map the algorithms to embedded software. They learn design flows from application theory to algorithm design to simulation in MATLAB and embedded software implementation in C. At various stages in the design flow, students explore and quantify design tradeoffs in signal quality vs. implementation for various algorithms. Applications include audio, image processing, biomedical instrumentation and communication systems.

The teaching assistants are Mr. Yunseong Cho and Mr. Sam Kanawati. Lab sections will meet in EER 1.810 at the following times: Mondays 6:30-9:30pm (Kanawati), Tuesdays 6:30-9:30pm (Cho), Wednesdays 6:30-9:30pm (Kanawati) and Fridays 1:00-4:00pm (Cho). The TAs will also hold weekly office hours on Wednesdays 4:30-6:00pm (Cho), Thursdays 3:30-6:30pm (Kanawati) and Thursdays 6:30-8:00pm (Cho). Students work in teams of two in the lab. A maximum of 12 students are in each lab section.

In the graduate curriculum, this course may be applied to an MSEE degree provided that it is taken for letter grade and a grade of at least B- is received. Up to two undergraduate courses may be applied toward an MSEE degree, subject to the approval of the curriculum track academic advisor. Undergraduate courses do not apply to the coursework requirements for a PhDEE degree.

The video recordings of lectures from spring 2014 are available on YouTube. These recordings along with the notes that you have taken in lecture would be helpful in reviewing lecture material.

Advice to get the most out of this course:

  1. Remove distractions that prevent you from being efficient in your work and in your play.
  2. When choosing courses, check the workload ratings by the two-thirds of students who had previously taken the course on the course instructor surveys.
  3. Write down questions in a journal when they arise and find opportunities to ask the questions to professors, TAs, tutors, students and others.
  4. Find a mutually beneficial study group of two or three persons for each course – more than three can become great for socializing but unproductive for studying.
  5. Attend instructor, teaching assistant and tutor office hours. They can answer your questions and guide you in what material to focus on when studying.
  6. Attend all lectures. It will save you time— the instructor will explain difficult concepts, indicate what material to focus on, and give insights not available elsewhere.
  7. Start assignments when assigned and make progress each day. This will give your brain more calendar time to process the information and reduce panic before the deadline.
Items 1, 3 and 4 came from students. A reference to support item 7 is: Nate Kornell, "Optimising learning using flashcards: Spacing is more effective than cramming", Applied Cognitive Psychology, vol. 23, no. 9, pp. 1297-1317.
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