Calculating Convolution Sum for Digital Signal Processing Class

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Discussion Overview

The discussion revolves around performing a convolution operation on two discrete-time signals as part of a Digital Signal Processing class. Participants are attempting to identify errors in the convolution process, particularly focusing on the folding operation and the interpretation of the signals involved.

Discussion Character

  • Homework-related
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant expresses concern that their folding operation may be incorrect, leading to an unexpected result in the convolution sum.
  • Another participant requests a complete problem statement to better understand the context of the convolution operation.
  • A participant questions the clarity of the signals presented, specifically the notation used for the signals and the implications of the folding operation.
  • One participant suggests visualizing the signals with a stem plot to better understand the convolution process and the relevant summation range.
  • There is mention of the need to clarify the definitions of the signals and the notation used, particularly regarding the unit step function.

Areas of Agreement / Disagreement

Participants do not appear to reach a consensus on the clarity of the problem statement or the correctness of the convolution steps. Multiple competing views regarding the interpretation and execution of the convolution operation remain present.

Contextual Notes

There are limitations in the clarity of the problem statement and the notation used for the signals, which may affect the understanding of the convolution process. The discussion also highlights the importance of visual representation in understanding discrete-time convolutions.

Who May Find This Useful

Students and practitioners in digital signal processing, particularly those interested in convolution operations and the interpretation of discrete-time signals.

wirefree
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TL;DR
What all does folding a signal entail?
Please see below my attempt to perform the convolution operation on two discrete-time signals as part of my Digital Signal Processing class.

0794916C-1F30-4331-A74D-CF4C5459220B.jpeg
I suspect my folding operation, i.e. flipping one signal about k=0, might be the cause.

Ostensibly the answer of the convolution sum evaluated at n=-2 should be 4/3.

Would appreciate if you can point out my error.

Thank you and Namaste
 
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wirefree said:
two discrete-time signals as part of my Digital Signal Processing class.
Care to share the complete problem statement with us ? Not just a snippet with rather random scribbles and no indication of what is wrapping and what is not, no logic, no punctuation, ... ?
 
BvU said:
Care to share the complete problem statement with us ?

Thank you for responding.
Hope today has been good one.

My apologies if the problem statement wasn’t ostensible. The two signals are in the first line; flipping, which is one of the steps of discrete-time convolution, occurs in the second.
Problem Statement: Perform convolution sum on the two signals shown in the first line.

Namaste.
 
wirefree said:
The two signals are in the first line; flipping, which is one of the steps of discrete-time convolution, occurs in the second.
Good :rolleyes: .

So line 1 has two signals. The first being sample(##n##) ##= 2^n [u(-n)]## and the second being ##2^{-n} [u(n+1)]## without further specification of ##u(n)## ?

How can 'flipping' (?) lead to line 2 ?

What is the relation between the third line and the preceding ones ?

And: how do I distinguish beween u, n and k in your handwriting ?

Then: I'm familiar with convolutions like
1573051250102.png

so I suppose your R is the equivalent of ##\tau## ?

## ##
 
Note that you are doing a discrete-time convolution. Try plotting (e.g., a stem plot) just the two step functions (i.e., u[n]). Look at them visually. One is reversed and the other is time shifted. Then decide which one you will reverse (i.e., flip) for the convolution operation. Do it, and look again visually. That will tell you the summation range that is relevant. Plug everything into the discrete-time convolution equation and evaluate. It is important to realize that step functions are used to limit the summation range for discrete convolutions and transforms. Have fun!

Edit - you will also need some useful expressions. See slide 2 of HERE
 
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