Introducing Machine Learning in a Sophomore Signals and Systems Course

Chao Wang, Abhinav DIxit, Andreas Spanias, Sunil Rao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


This Innovative Practice Work in Progress Paper describes the experience and assessment of introducing machine learning concepts in a sophomore signals and systems course. Advanced machine learning concepts are typically covered in graduate level courses. However, as machine learning applications become more and more ubiquitous in our daily lives, it is important to expose students to machine learning concepts early at the undergraduate level. Signals and Systems I is a sophomore level course in the Electrical Engineering online bachelor degree curriculum. As the first course in signals and systems, it focuses on the basic concepts including signal transformation, linear time-invariant systems, Fourier series, Fourier transforms, Laplace and Z transforms. The course was taught using lecture videos and reading materials. MATLAB labs were also incorporated to introduce students to practical applications. Feedback from students showed their preference for more real world applications. This paper describes how a web-based simulation lab exercise was introduced to expose students to machine learning concepts. Specifically, students made the connection between machine learning and signals and systems concepts through a speech recognition application. In particular, students applied spectral analysis and identified voice features through pole/zero representation. To evaluate the effectiveness of the exercise, statistics from pre/post quizzes as well as student comments from a survey is analyzed.

Original languageEnglish (US)
Title of host publication2019 IEEE Frontiers in Education Conference, FIE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728117461
StatePublished - Oct 2019
Event49th IEEE Frontiers in Education Conference, FIE 2019 - Covington, United States
Duration: Oct 16 2019Oct 19 2019

Publication series

NameProceedings - Frontiers in Education Conference, FIE
ISSN (Print)1539-4565


Conference49th IEEE Frontiers in Education Conference, FIE 2019
Country/TerritoryUnited States


  • Electrical Engineering
  • Laboratory Experiences
  • Machine Learning
  • Online Education
  • Signals and Systems
  • Speech Processing Introduction

ASJC Scopus subject areas

  • Software
  • Education
  • Computer Science Applications


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