Exponentially Modified Gaussian

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Discussion Overview

The discussion revolves around fitting a detector response using an Exponentially Modified Gaussian in Matlab. Participants are exploring the mathematical formulation and convolution involved in deriving the function y(t) from given h(t) and f(t) functions. The focus includes theoretical aspects and practical implementation in a computational context.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents the equations for h(t) and f(t) and describes the convolution process to derive y(t), expressing difficulty in obtaining the expected result.
  • Another participant suggests that limits of integration for t' need to be specified to properly evaluate the convolution.
  • A different participant mentions the necessity of completing the square for terms in the exponent to derive the variable for the error function (erf), indicating ongoing challenges in this process.

Areas of Agreement / Disagreement

Participants express differing views on the steps required to derive y(t), with some suggesting additional mathematical manipulations while others focus on the integration limits. The discussion remains unresolved as participants continue to explore their approaches.

Contextual Notes

There are indications of missing assumptions regarding the integration limits and the specific form of the equations. Participants have not reached a consensus on the correct method to complete the square or the final form of y(t).

James_1978
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I am fitting a detector response using Matlab. I have been asked to fit the spectrum using a Exponentially Modified Gaussian. This is as follows.

[ tex ] a^x_n [ /tex ]

h(t) = [ tex ] \frac{A}{\sqrt{2 \pi} \sigma} e^{-\frac{(t-t_{R})^{2}}{2\sigma^{2}} [ /tex ]

f(t) = [ tex ] \frac{1}{\tau}e^{-\frac{t}{tau}}[ /tex ]

Using the convolution y(t) = [ tex ] \int^{\infinity}_{0} h(t^{\prime})f(t-t^{prime})dt^{\prime}[ /tex ]

This gives y(t) = [ tex ] \frac{A}{\tau \sigma \sqrt{2 \pi}} \int^{\infinity}_{0}} e^{-{\frac{(t-t_{R} - t^{\prime})^{2}}{2\sigma^{2}}e^{\frac{-t^{\prime}}{tau}} [ /tex ]

This is the convolution of h(t)*f(t) to give y(t)

The answer is

y(t) = [ tex ] \frac{A}{2 \tau}[1-erf(\frac{\sigma}{\sqrt{2}\tau} - \frac{t-t_{R}}{\sqrt{2}\sigma]e^{\frac{\sigma^{2)}{\sqrt{2}\tau} - \frac{t-t_{R}}{\tau}}[ /tex ]

I have been unable to get the answer. Has anyone ever worked this out to get y(t)? Also this is my first post and I am not sure how to get the latex to appear?
 
Last edited:
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James_1978 said:
I am fitting a detector response using Matlab. I have been asked to fit the spectrum using a Exponentially Modified Gaussian. This is as follows.

h(t) = \frac{A}{\sqrt{2 \pi} \sigma} e^{-\frac{(t-t_{R})^{2}}{2\sigma^{2}}

f(t) = \frac{1}{\tau}e^{\frac{t}{\tau}}

Using the convolution y(t) = \int^{\infinity}_{0} h(t^{\prime})f(t-t^{\prime})dt^{\prime}

This gives y(t) = \frac{A}{\tau \sigma \sqrt{2 \pi}} \int^{\infinity}_{0} e^{-{-\frac{(t-t_{R} - t^{\prime})^{2}}{2\sigma^{2}}e^{\frac{t^{\prime}}{\tau}}

This is the convolution of h(t)*f(t) to give f(t)

The answer is

y(t) = \frac{A}{2 \tau}[1-erf(\frac{\sigma}{\sqrt{2}\tau} - \frac{t-t_{R}}{\sqrt{2}\sigma})]e^{\frac{\sigma^{2}}{\sqrt{2}\tau} - \frac{t-t_{R}}{\tau}}

I have been unable to get the answer. Has anyone ever worked this out to get y(t)? Also this is my first post and I am not sure how to get the latex to appear?

You must write your equations between
 
Last edited:
You need to prescribe the limits of integration on t'.
 
Yes...but I believe one must complete the square for the terms in the exponent. This gives you the z for the erf(z). However, I am unable to complete the square correctly. I am close and still working on it.
 

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