A New Experiment-Based Way to Introduce Fourier Transform and Time Domain–Frequency Domain Duality

This paper describes a complex multistep problem exercise used in a problem-based learning (PBL) context to introduce the fundamentals of the Fourier transform (FT) and convey the concept of the time domain-frequency domain duality. This complex problem exercise (CPE) consists of obtaining the frequency response (network function) of an RC circuit from voltage measurements taken during the charge/discharge transient and is carried out in circuits, electronics, and electromagnetism laboratories. Although it is widely accepted that undergraduate students should be introduced to FT, this involves substantial and complex mathematics. In order to avoid this difficulty, the discrete Fourier transform (DFT) is used as an approximation to the FT because it is easier to use in a computational environment. The CPE uses a practical approach to concepts such as impulse response, sampling theorem, Nyquist frequency, aliasing, and uncertainty and causality principles; it is thought to be of pedagogical interest as an introduction to the FT. In particular, it could be of interest to instructors and undergraduate students taking courses in circuit theory, electromagnetic theory, linear systems, and digital signal processing in electrical engineering or similar degree programs.

[1]  Johanna Leppävirta,et al.  Complex Problem Exercises in Developing Engineering Students' Conceptual and Procedural Knowledge of Electromagnetics , 2011, IEEE Transactions on Education.

[2]  Richard C. Dorf,et al.  Introduction to Electric Circuits , 1989 .

[3]  K. T. Chau,et al.  A software tool for learning the dynamic behavior of power electronics circuits , 1996 .

[4]  Matthew N. O. Sadiku,et al.  Elements of Electromagnetics , 1989 .

[5]  Levent Sevgi,et al.  Numerical Fourier Transforms: DFT and FFT , 2007, IEEE Antennas and Propagation Magazine.

[6]  Gerald Kaiser,et al.  A Friendly Guide to Wavelets , 1994 .

[7]  Yu Zhang,et al.  Time and Frequency Domain Solutions of EM Problems: Using Integral Equations and a Hybrid Methodology , 2010 .

[8]  Charles H. Patterson,et al.  Two approaches to teaching computation physics , 2002, Comput. Sci. Eng..

[9]  T. J. Cavicchi,et al.  Experimentation and analysis: SigLab/MATLAB data acquisition experiments for signals and systems , 2005, IEEE Transactions on Education.

[10]  C. S. Burrus Teaching the FFT using Matlab , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[11]  Michael J. Corinthios Signals, Systems, Transforms, and Digital Signal Processing with MATLAB , 2009 .

[12]  Sanjit K. Mitra,et al.  Digital Signal Processing: A Computer-Based Approach , 1997 .

[13]  Milka M. Potrebic,et al.  Understanding Computation of Impulse Response in Microwave Software Tools , 2010, IEEE Transactions on Education.

[14]  Dylan Dah-Chuan Lu,et al.  An Analog Computer for Electronic Engineering Education , 2011, IEEE Transactions on Education.

[15]  Sen M. Kuo,et al.  Fast Fourier Transform and Its Applications , 2002 .

[16]  Stephen A. Dyer,et al.  Digital signal processing , 2018, 8th International Multitopic Conference, 2004. Proceedings of INMIC 2004..

[17]  M. Pollock Basic Mechanics: Learning by Teaching – an increase in student motivation (a small scale study with Technology Education students) , 2005, Proceedings Frontiers in Education 35th Annual Conference.

[18]  Norman Chonacky,et al.  3Ms for Instruction, Part 2: Maple, Mathematica, and Matlab , 2005, Computing in Science & Engineering.

[19]  Leo P. Ligthart,et al.  Antenna time-domain measurement techniques , 1997 .

[20]  Rudi van Drunen,et al.  Localization of Random Pulse Point Sources Using Physically Implementable Search Algorithms , 2020, Optoelectronics, Instrumentation and Data Processing.

[21]  P. vandenBerg,et al.  General Assembly Special Session: Time-Domain vs. Frequency Domain Methods , 1995, IEEE Antennas and Propagation Magazine.