Finding the Probability Density Function for the Sum of Two Random Variables

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Discussion Overview

The discussion revolves around finding the probability density function for the sum of two random variables, specifically a complex random variable X and a constant Y. The focus includes theoretical aspects of probability distributions and the application of Fourier transforms in this context.

Discussion Character

  • Exploratory, Technical explanation, Debate/contested

Main Points Raised

  • One participant describes a random variable X defined as X = a*e(j*phi), where phi is uniformly distributed over [0, 2pi), and seeks to find the probability density function of Z = X + Y, with Y being a constant.
  • Another participant clarifies that if j represents the imaginary unit (i), then X is uniformly distributed on a circle of radius a, and Z would also be uniformly distributed on a circle of radius a centered at b.
  • A later reply mentions that after simulating the distribution in MATLAB, the participant observed that Z appeared to resemble an upside-down Gaussian distribution centered around pi, questioning if this observation is correct.
  • Another participant expresses confusion regarding the nature of Z, noting that it is a complex variable rather than a real one.

Areas of Agreement / Disagreement

Participants express differing views on the nature of the distribution of Z, with some suggesting it is uniformly distributed while others question the implications of Z being a complex variable. The discussion remains unresolved regarding the correct interpretation and characteristics of the distribution.

Contextual Notes

There is a lack of clarity regarding the treatment of complex variables in the context of probability density functions, and assumptions about the nature of Z may not be fully addressed.

jmckennon
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Hi,

I've been working on this problem but I feel like I'm over complicating it. If you have a random variable X= a*e(j*phi), where phi is uniform on the interval [0,2pi) and a is some constant, and another random variable Y= b where b is a constant. I'm looking to find the probability density function of the random variable Z=X+Y.

This is probably really simple but from what I've been trying to do, I can just take the Fourier transform of X, Fourier transform of Y multiply them, and then take the inverse Fourier of that, but it doesn't seem to work. How can I do this?
 
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You haven't defined j. If I can assume you mean i (sqrt(-1)), then X (complex variable) is uniformly distributed on a circle of radius a, centered at 0. Z is then uniformly distributed on a circle of radius a centered at b.
 
yes, i apologize, j is sqrt(-1). After defining in MATLAB phi=rand(1,M).*2*pi where M=1000, i plotted Z= b+a.*exp(j.*phi) for various values of a and b and it looked kinda like an upside gaussian distribution centered about pi. Is this right?
 
*upside down gaussian distribution
 
I'm confused about what you did, since Z is complex, not real.
 

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