Convolution in Digital Signal Processing
Updated 27 Jan 2022
Created with R2021a. Compatible with R2021a and later releases.
This package contains live scripts and supporting data files centered around the fundamentals of convolution in digital signal processing. These materials are designed to be flexible and can be easily modified to accommodate a variety of teaching and learning methods. Used in a sequence, the live scripts progressively add depth to the topic. However, each script can be easily adapted for standalone use. We include a brief background, interactive illustrations, tasks, reflection questions, application examples, and guided exercises for the different concepts explored.
The instructions inside the live scripts will guide you through the activities and exercises. Get started with each live script by running it one section at a time. To stop running the script or a section midway (for example, when an animation is in progress), use the Stop button in the Run section of the Live Editor tab in the MATLAB toolstrip.
MATLAB Onramp – a free two-hour introductory tutorial to learn the essentials of MATLAB®.
- Define and compute convolution of two 1-D signals.
- Use FFT to compute convolution.
- Define and compute circular convolution.
- Achieve equivalence between circular and linear convolution.
Products: MATLAB, Signal Processing Toolbox™
- Identify the moving average operation as a simple LTI system.
- Define an LTI system.
- Compute the output of an LTI system for an arbitrary input signal given its impulse response.
Data files: 1st_baptist_nashville_balcony.wav, ringtone.wav
The audio file 1st_baptist_nashville_balcony.wav by Adam Townsell is licensed under CC BY 4.0 and was obtained from https://openairlib.net/.
Products: MATLAB, Signal Processing Toolbox
- Explain the frequency domain implications of convolving two signals in the time domain.
- Achieve equivalence between low pass filtering and convolution.
- Define and compute convolution of two 2-D signals.
- Perform spatial filtering of images to achieve effects such as blurring and embossing.
Data files: lettert.png, flower.jpg
Products: MATLAB, Signal Processing Toolbox, Image Processing Toolbox™ (optional), Deep Learning Toolbox™ (optional)
The license for this module is available in the LICENSE.TXT file in this GitHub repository.
Have any questions or feedback? Contact the MathWorks online teaching team.
Copyright 2021 The MathWorks, Inc.
Emma Smith Zbarsky (2022). Convolution in Digital Signal Processing (https://github.com/MathWorks-Teaching-Resources/Convolution-Digital-Signal-Processing/releases/tag/v1.2.1), GitHub. Retrieved .
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