Discrete-Time Convolution and System Properties (Classroom Lecture #8, 2018)
3,664 views · Published 5 August 2018 · 1:39:18 · Indexed 27 September 2026
Channel: Adam Panagos · 2018 · Education
http://adampanagos.org This is the first ever LIVE classroom lecture that I've made available publicly on my channel so I'm interested to get some feedback from everyone. I have many more videos like this I could share, so if you like this style of video please comment below. If you think I should stick with my typical video format (e.g. short videos recorded on my iPad) let me know that as well. This video did take a decent amount of time to prepare (i.e. edit/trim content, make a table of contents, etc.) so I would like to know if this type of video is useful before I invest time in making more. Let me know what you think! 0:00:05 - Review of Last Lecture The first few minutes of the video review concepts and topics from the previous classroom lecture. This previous video is not posted yet but based on the feedback on this video I can keep adding more if requested. 0:05:20 - Convolution Properties Properties of discrete-time convolution to include the associative, distributive, commutative, and time-shifting properties are defined and discussed. 0:14:37 - Convolution Sum Example The first convolution sum example works with two very short discrete-time signals. As such, we can easily evaluate the convolution summation by simply "writing out" each term of the expression and adding everything up. 0:31:42 - Reflect, Shift, and Sum Convolution Example #1 The reflect, shift, and sum approach is a more general approach used for computing the convolution of two signals when we have mathematical equations/expression for the two signals. 0:49:07 - Reflect, Shift, and Sum Convolution Example #2 Another discrete-time convolution example that uses the same RSS approach. 1:11:26 - Analytic Approach In this section, we look at using a table of discrete-time convolution pairs to compute the convolution of two signals. This is a much quicker way of computing the convolution of two signals, but obviously it only works if the tables you're working with are in the table. If they aren't, you'll probably have to use the reflect, shift, and sum approach. If you enjoyed my videos please "Like", "Subscribe", and visit http://adampanagos.org to setup your member account to get access to downloadable slides, Matlab code, an exam archive with solutions, and exclusive members-only videos. Thanks for watching!
