Inverse Discrete Laplace Transform

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SUMMARY

The discussion centers on the concept of modifying the Discrete Fourier Transform (DFT) by introducing an additional variable, sigma, to create a new function that resembles the z-transform. The user explores whether iterating over a range of sigmas while computing the DFT of an impulse response would yield a surface plot similar to the transfer function of the system. However, it is clarified that this approach does not parallel the relationship between the Continuous Time Fourier Transform (CTFT) and the DFT, as the DFT is specifically a mapping between discrete domains, while the z-transform generalizes the Discrete Time Fourier Transform (DTFT).

PREREQUISITES
  • Understanding of Laplace Transform and its properties
  • Familiarity with Discrete Fourier Transform (DFT) and its applications
  • Knowledge of z-transform and its relationship to the DFT
  • Basic concepts of impulse response in systems theory
NEXT STEPS
  • Study the properties and applications of the z-transform
  • Explore the differences between the Discrete Time Fourier Transform (DTFT) and the DFT
  • Investigate the implications of adding exponential decay terms in Fourier analysis
  • Learn about surface plots in the context of system transfer functions
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Engineers, mathematicians, and researchers involved in signal processing, control systems, and those interested in advanced Fourier analysis techniques.

swraman
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Hi,

I have an idea which when tested looks like its clearly flawed. I am hoping someone can tell me where my procedure is flawed, or point me to some other theory that has already done something similar.

laplace_fourier.png
The first two are the laplace transform.
The third line is the Fourier Transform.
The last line is the Discrete Fourier transform.

Im looking at lines 2 and 4 (along with how 3 - the Fourier transform is related to 4). Is there anything stopping me from modifying the Discrete Fourier transform by adding in an extra variable sigma to the loop - an exp(-sigma*n/N) term - and iterating over a range of sigmas. That is, each Sigma would result in one "DFT".

If I do this process with an input time function h(t) equal to the impulse response of a system - that is compute the "DFT" over a range of sigma's. Then, if I place each of these "DFT"s together into a surface plot, should it not look like the transfer function plot of the system (represented by impulse response h(t) )?

I would expect to see the magnitude of the "DFT"s to spike to infinity at the value of sigma and omega representing the poles of the system whose impulse response is h(t). I used a simple 2-DOF system to generate an impulse response, then ran this process across a range of sigmas (my natural frequency was well within my sampling parameters' capability). But as I said, the result doesn't look like I expected..

Is there something incorrect with my thinking here?

Thanks
 
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Why would you do 2 and what do you think is new about it? It is just the continuation of the Laplace (or Fourier) transform to the complex plane...
 
I just added eqn (2) to show how similar the Laplace transform is to the Fourier transform (which has a well defined Discrete cousin in the DFT). I know there's nothing new about it.

The thinking was: If (4) is the discretized version of (3), why can we not generate another function that is a discretized version of (2) by adding in the extra exponential decay term into (4)?
 
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What you have described is called the z-transform. But it does not parallel the Continuous Time Fourier Transform (CTFT) to Discrete Fourier Transform (DFT) relationship exactly. The DFT maps between two discrete domains corresponding to sampling of f(t) and F(ω). If one were to take the Discrete Time Fourier Transform (DTFT - note this is NOT the DFT!) which is a mapping of the sampled f(t) in the ω domain and then generalize it you would in fact have the Z-transform.
 
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