Solve Convolution Systems: Integrate Impulse Response & Input

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    Convolution Systems
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Discussion Overview

The discussion revolves around the application of convolution in systems, specifically focusing on the integration of an impulse response and an input signal. Participants explore the mathematical formulation of convolution and its implications for system output.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents the impulse response and input signal, proposing a method for calculating the system output through convolution.
  • Another participant challenges the initial convolution formula, asserting that it does not align with the standard definition and provides an alternative formulation.
  • Some participants discuss the commutative property of convolution and its relevance to the problem at hand.
  • A participant suggests a logical progression in the integration process, leading to a conclusion about the area under the function for different ranges of t.
  • There is a mention of the assumption that the limits of convolution are taken between 0 and t, which is typically accepted in the context of systems.

Areas of Agreement / Disagreement

Participants express differing views on the correct formulation of the convolution integral and its limits. There is no consensus on the approach to the problem, as some participants challenge the initial claims while others build upon them.

Contextual Notes

Participants note that the convolution limits are usually assumed to be between 0 and t, but the applicability of this assumption to the specific problem is questioned. The discussion includes various interpretations of the integration steps and their implications for the output.

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Hi everyone, I'm having some trouble understanding how convolutions are applied to systems.

Suppose I'm given the impulse response of a system as ##g(t) = u(t)## and I'm also given the system input ##x(t) = u(t) - u(t-2)##.

The system output should then be given by:

$$y(t) = g(t) * x(t) = \int_0^t g(t - x) x(x) \space dx = \int_0^t u(t-x)u(x) \space dx - \int_0^t u(t-x)u(x-2) \space dx$$

The integrals should reduce to this I think:

$$\int_0^t u(t-x) \space dx - \int_2^t u(t-x) \space dx$$

How do I finish this integration? I thought about setting ##v = t - x##, but I am unsure.
 
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Svein said:
Your convolution formula is not according to the standard (https://en.wikipedia.org/wiki/Convolution). It should be y(t)=g(t)*x(t)=\int_{-\infty}^{\infty}g(z)x(t-z)dz=\int_{-\infty}^{\infty}u(z)(u(t-z)-u(t-z-2))dz.

Why would this matter? The convolution is a commutative operation: ##f*g = g*f##.

Also, in the context of systems it is usually taken for granted that ##0 \leq t < \infty## and the convolution limits are taken between ##0## and ##t##.

I believe I have figured out the next logical step in the integration:

$$\int_0^t u(t-x) \space dx - \int_2^t u(t-x) \space dx = \int_0^2 u(t-x) \space dx$$

Okay wait then the area under this function for ##t \geq 2## would simply be equal to ##2##. It would be equal to ##t## for ##0 \leq t \leq 2##.

Therefore:

$$\int_0^2 u(t-x) \space dx = t[u(t) - u(t - 2)] + 2u(t - 2) = tu(t) + [2 - t]u(t - 2)$$

I guess the answer was to think about the area under the function.
 
Last edited:
Zondrina said:
Why would this matter? The convolution is a commutative operation: fg=gff*g = g*f.
I do not question that. What I did was to use the definition of convolution on your problem.
Zondrina said:
Also, in the context of systems it is usually taken for granted that 0≤t<∞0 \leq t < \infty and the convolution limits are taken between 00 and tt.
Maybe - but you need to show that this is applicable to the problem.
 

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