Virtual Conference
July 26, 2021
July 26, 2021
July 19, 2022
Electrical and Computer
13
10.18260/1-2--37294
https://peer.asee.org/37294
907
Thomas Moon received the B.S. degree in electrical electronic engineering from Pohang University of Science and Technology (POSTECH), Pohang, Korea, in 2008, and the Ph.D. degree in electrical and computer engineering from Georgia Institute of Technology, Atlanta, GA, USA in 2015. Between 2015 and 2017, he worked at IBM in Burlington, Vermont where he developed mmWave test equipment as a principle development engineer. He joined Coordinated Science Lab, University of Illinois at Urbana-Champaign (UIUC), IL, USA in 2017 as a post-doctoral researcher. He has been a Teaching Assistant Professor at Department of Electrical and Computer Engineering at UIUC. His current research interests include wireless sensing and communication in mmWave.
The rapid development of embedded systems brings new opportunities for modernized real-time digital signal processing (DSP) education. This paper introduces a novel real-time DSP laboratory course that aims to give students hands-on experience with real-time embedded systems using Android tablets at an early stage of their careers. The students will broaden and deepen their understanding of basic DSP theory and techniques and learn to relate this understanding to real-world observations and applications. The students will learn industrially-relevant skills such as rapid design prototyping in Python and Android development of DSP applications in C++/Java for computationally-constrained mobile devices. The course advances in two phases: structured labs and team projects. In the first halves of the course, a series of structured labs are provided to implement and analyze real-time DSP systems that utilize fundamental DSP concepts acquired in the introductory signal processing course. The fundamental concepts include topics such as FIR and IIR filtering, multi-rate processing, sampling, windowing, and spectral analysis. The remaining weeks in the course will be on implementing and simulating a DSP algorithm of a student's choice from a set of seminal DSP papers such as adaptive filtering, pitch detection, edge-aware filtering, motion tracking, pattern recognition, etc. The team project revolves around the development, testing, presentation, and documentation to help the students defend their proposed design and receive feedback from the teaching staff. We have offered this course for four years, and the student's feedback in the form of survey questionnaires has confirmed that this course has been successful.
Moon, T., & Do, M. N. (2021, July), Implement Your DSP Algorithm on Android Tablet: Real-time DSP Laboratory Course Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37294
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