Graphical Convolution in Physics & Electrical Engineering

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Discussion Overview

The discussion revolves around the use of graphical convolution in physics and electrical engineering, particularly in the context of signal processing and quantum mechanics. Participants explore the conditions under which graphical convolution is applied compared to traditional mathematical methods, addressing both theoretical and practical implications.

Discussion Character

  • Exploratory, Debate/contested, Conceptual clarification

Main Points Raised

  • One participant notes that graphical convolution is observed in both signal processing and quantum mechanics, questioning its application when functions are not causal or not equal to zero for t<0.
  • Another participant asserts that graphical convolution can be used for all types of signals, suggesting that its applicability is not limited by the causal nature of the functions.
  • A different participant raises the point that graphical convolution is often not utilized in math and physics courses, speculating that this might be due to the assumption that h(t) and f(t) equal 0 for t<0.
  • Some participants express the view that mathematical solutions are preferred in academic settings, implying that graphical methods may be seen as less rigorous or efficient.
  • There is a reiteration that graphical convolution can be applied regardless of the values of h(t) or f(t) for t<0, challenging the notion that such conditions limit its use.
  • Participants discuss the perception that mathematical methods are simpler and quicker, noting a lack of emphasis on graphical convolution in non-electrical engineering courses.

Areas of Agreement / Disagreement

Participants express differing views on the applicability of graphical convolution, with some asserting it can be used universally while others suggest limitations based on the assumptions about function values. The discussion remains unresolved regarding the reasons for the limited use of graphical convolution in academic contexts.

Contextual Notes

Participants mention assumptions regarding the values of functions for t<0, but do not resolve how these assumptions affect the use of graphical convolution. There is also a lack of consensus on the efficiency and appropriateness of graphical versus mathematical methods in various contexts.

sed199
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As a double major in physics an electrical engineering, I noticed that graphical convolution is used in both signal processing and quantum mechanics. In my signals course I couldn't help but notice that sometimes the professor would just convolved the function from straight integration, and other times we will have to break the integral into different intervals using Graphical convolution method. The graphical method seems more like a general way of solve convolution problems. Is graphical convolution used when the functions you are to be convolved aren't causal, or that the functions aren't equal to zero when t<0?
 
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it doesn't matter. . .you can use graphic convolution for all type of signals .
 
reddvoid said:
it doesn't matter. . .you can use graphic convolution for all type of signals .

But in most math and physics courses graphical convolution isn't used. Is that because it's assumed that h(t) and f(t) are assumed to equal 0 for t<0?
 
while in maths u r supposed to solve it mathematically, that's why graphical method is not used i think. . .
but h(t) or f(t) need not to be 0 for t<0 to use graphical convolution. . .
 
reddvoid said:
while in maths u r supposed to solve it mathematically, that's why graphical method is not used i think. . .
but h(t) or f(t) need not to be 0 for t<0 to use graphical convolution. . .

Graphical convolution can be used in any case, but the mathematical method seems much more simpler and quicker, and I noticed that graphical isn't used much at all in non-electrical engineering courses. Is that because we assume that f(t) and h(t) = 0 for t<0 for math examples?
 

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