Convolution integral and fourier transform in linear response theory

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Discussion Overview

The discussion revolves around the convolution integral in the context of linear time-invariant (LTI) systems, specifically examining two formulations of the convolution integral for determining the output of the system. Participants explore the implications of initial conditions, causality, and the transition from the frequency domain to the time domain using Fourier transforms.

Discussion Character

  • Technical explanation, Conceptual clarification, Debate/contested

Main Points Raised

  • One participant presents two formulations of the convolution integral for LTI systems and questions the importance of initial conditions and causality in choosing between them.
  • Another participant asserts that there is only one definition of the convolution integral that extends from -∞ to ∞, suggesting that specific time limits depend on the problem context.
  • A third participant clarifies that for a causal system, the convolution integral can be limited to the range from -∞ to t, as contributions from negative times do not affect the output.
  • The original poster expresses a preference for working in the frequency domain and seeks guidance on which convolution integral to use for transitioning from frequency to time domain.

Areas of Agreement / Disagreement

Participants exhibit disagreement regarding the necessity of limiting the convolution integral to specific time ranges, with some advocating for the general form while others suggest context-dependent limits. The discussion on causality and its implications for the choice of convolution integral remains unresolved.

Contextual Notes

Participants note that the choice of convolution integral may depend on the system's causality and the specific context of the problem, but these factors are not fully resolved in the discussion.

kgz
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Hello,

Consider I have a linear time-invariant (LTI) system, with ##x(t)##, ##y(t)##, and ##h(t)##, as input, output, and impulse response functions, respectively.
I have two choices to write the convolution integral to get ##y(t)##:
$$ 1)\ \ \ y(t) = \int_{0}^{t} h(t-t')x(t')dt' $$
and
$$ 2)\ \ \ y(t) = \int_{-\infty}^{t} h(t-t')x(t')dt' .$$
What are the differences between these two, and are initial conditions important factors in the decision of choosing one of these? Is it related to causality of the system?

Also, suppose I am just given the frequency response of the system,
$$ Y(\omega)=H(\omega)X(\omega) . $$
Using Fourier transform and convolution integral theory, I want to change from frequency domain to time domain. Which one of the convolution integrals above should I pick?
Because I need to work in the freuqency domain, I am trying not to use Laplace transform.

Thank you for sharing your ideas.
 
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No, there is only one definition of convolution integral and it extends from -∞ to ∞. Specific times like 0 only have meaning in relation to the specifics of your problem (for instance, the input might be turned on at t=0).
 
As marcus noted, for your linear time-shift invariant system the convolution integral in generality must be ##y(t) = \int_{-\infty}^{\infty}h(t - t')x(t')dt'##. Now if your system happened to be causal and you wanted the response at ##t## then you can write ##y(t) = \int_{-\infty}^{t}h(t - t')x(t')dt'## only because for a causal system, the response at ##t## will only depend on past contributions up to ##t## i.e. ##h(t - t')## vanishes for negative arguments. marcus explained the ##t = 0## part so I'll leave it at that.
 
Thank you guys for your responses.
 

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