Analyzing Convolution of Exponential Functions with Unit Step Function

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Discussion Overview

The discussion revolves around the convolution of exponential functions with the unit step function, specifically focusing on the mathematical process and implications of such convolutions. Participants explore various approaches and examples, including specific functions and contexts related to signal processing and tracer kinetics modeling.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • Some participants inquire about the convolution of exp(x(n)) * u(x(n)) and exp(x(n-1)) * u(x(n-1)), expressing confusion over the notation and the implications of x(n) being inside the unit step function.
  • One participant provides a detailed example of convolution involving h(t) = e^{-t} * u(t) and f(t) = e^{-2t} * u(t), calculating y(1) and discussing the integral involved.
  • Another participant suggests that understanding the properties of convolution might help manipulate the equation, indicating a potential alternative approach.
  • A new participant introduces a related question about convolving an arbitrary input function with a piecewise function defined as the Impulse Residue Function, seeking insights into this specific application.
  • There is a mention of MATLAB code for convolution in the z domain, although a later reply indicates a preference for analytical solutions over numerical ones, emphasizing the importance of understanding the underlying concepts.

Areas of Agreement / Disagreement

Participants express varying levels of understanding and approaches to the convolution problem, with some seeking clarification on notation and others providing examples. There is no consensus on the correct method or interpretation of the functions involved, indicating ongoing debate and exploration.

Contextual Notes

Some participants note the difficulty in addressing the convolution due to the specific form of x(n) within the unit step function, suggesting that additional information about x(n) is necessary for clarity. The discussion also touches on the application of convolution in different contexts, such as tracer kinetics modeling.

purplebird
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How do you do the convolution of

exp (x(n))*u(x(n)) and exp(x(n-1))*u(x(n-1))

where u(x) is the unit step function. Thanks.
 
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purplebird said:
How do you do the convolution of

exp (x(n))*u(x(n)) and exp(x(n-1))*u(x(n-1))

where u(x) is the unit step function. Thanks.

Because convolution is commutative,
y(t) = u(t) * e^{t} = e^{t} * u(t)
therefore, using the general result
h(t)*u(t) = \int_{-\infty} ^{t} *e^{\tau} d\tau= e^{t} - e^{-\infty } = e^{t}

So, as an example given that

h(t) = e^{-t}*u(t)
f(t) = e^{-2t}*u(t)

and y(t) = h(t)* f(t) , determine y(1).

Solution,

y(t) = \int_{-\infty} ^{\infty} h(\tau)f(t-\tau) d\tau = \int_{-\infty} ^{\infty} [e^{-\tau}u(\tau)] [e^{-2(t-\tau)} u(t - \tau)] d\tau

for any value of t, it fallows that
y(1) = \int_{-\infty} ^{\infty} [e^{-\tau}u(\tau)] [e^{-2(1-\tau)} u(1 - \tau)] d\tau = \int_{0} ^{1} e^{-\tau}e^{-2(1-\tau) }d\tau = e^{-2}(e^1 - 1)=e^{-1}-e^{-2} \approx 0.233.

I hope this helps a little bit.


Reference. Convolution examples from Kudeki and Munson
 
purplebird said:
How do you do the convolution of

exp (x(n))*u(x(n)) and exp(x(n-1))*u(x(n-1))

where u(x) is the unit step function. Thanks.

Wait, the x(n) is inside the u(x)? That makes it difficult to do, unless you tell us something more about what x(n) looks like.

Are you sure it's not supposed to be just u(n)?
 
quadraphonics said:
Wait, the x(n) is inside the u(x)? That makes it difficult to do, unless you tell us something more about what x(n) looks like.

Are you sure it's not supposed to be just u(n)?

You are right, the other approach will be maniopulate the equation with the properties of convolution.
 


Nice Job!

I am new here and I bring a similar question for my first post...

I want to know how to do a convolution where the two functions are:

Ca(t) - arbitrary Input function
(it actually represents the time activity curve of a CT contrast bolus injection in the blood)

R(t) - a piecewise function defined as follows:

R(t) = 1, 0<t<Tm
and E*(exp)^(kt), t>Tm

(this R(t) is called the Impulse Residue Function for the Johnson WIlson model for capillary tracer exchange)

so therefore:

Ca(t)*R(t) = (from 0 to Tm){Ca(t) convolved with 1} + (from Tm to t)E*{Ca(t) convolved with (*exp)^(-kt)}

Can anyone shed some light on this please?!

If anyone is curious the context of this convolution is for determining the representation of CT tissue attenuation in tracer kinetics modelling, considering a distributive parameter model. A background link for those interested is below.

http://www.minervamedica.it/index2.t?show=R39Y2003N03A0171

 
what is MATLAB code for convolution in z domain?
 
Nevermind, I worked this thing out

I don't want Matlab code I just wanted to do it by hand, an analytical solution

Matlab is worthless for giving insight into a solution, but it will provide you with a numerical solution...if you don't understand how it works and why it works the solution is useless for understanding your problem
 

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