Test using continuous uniform pdf instead of Gaussian distribution pdf

[xbosch]

First of all good job with the code. I ported to Matlab and I could not find any error or problem.

The only issue that I have seen is when you test the PFB you use np.random.random() to generate noise. np.random.random has a uniform probability density function (pdf), according to the Numpy webpage:

Results are from the “continuous uniform” distribution over the stated interval. [0,1] by defeault

Thermal noise, which is what you want to simulate to emulate RF noise, has a Gaussian pdf. To simulate Gaussian noise you should use np.random.randn() instead, according to the Numpy webpage:

randn generates an array of shape (d0, d1, ..., dn), filled with random floats sampled from a univariate “normal” (Gaussian) distribution of mean 0 and variance 1

This code issue is in both the .py and the jupyter notebook.

Best Wishes!

[telegraphic]

Hey @xbosch, thanks for checking it out, glad you found it useful! Agreed that Gaussian noise should be used, will update accordingly.

By the way, please feel free to push your MATLAB code if you're interested (repo license is CC-BY 4)

[texadactyl]

@telegraphic Fixed in PR #6. I used a numpy normal distribution function (random.normal) which has more parameter options. My guess is that you still wanted the distribution centered around 0.5 spread from 0 to 1 to get the desired noise values.

[telegraphic]

Hi @texadactyl, fancy seeing you here! Thanks, merged.

[texadactyl]

I try to never miss a chance to learn something new or relearn in a new way.

Looking at Julia, its easy to convert first-hand code; even numpy functions are built-in (how efficient?). It is quite another matter to identify which libraries to use in place of scipy. Probably Julia's "DSP".

[xbosch]

Guys, I have the codes in matlab, I can send them to you if you are interested XB

On Sun, Sep 20, 2020 at 6:24 AM Richard Elkins notifications@github.com wrote:

I try to never miss a chance to learn something new or relearn in a new way.

Looking at Julia, its easy to convert first-hand code; even numpy functions are built-in (how efficient?). It is quite another matter to identify which libraries to use in place of scipy. Probably Julia's "DSP".

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/telegraphic/pfb_introduction/issues/4#issuecomment-695786930, or unsubscribe https://github.com/notifications/unsubscribe-auth/ABBGKYFEW7CAWZPOJRT4EQTSGX675ANCNFSM4L3F5BZA .

-- Se'n va la primavera. Ploren les aus i son llàgrimes els ulls dels peixos.

Matsuo Bashö

[texadactyl]

@xbosch It was simple to fix.

[xbosch]

Hi,

That is right. It is not clear what is the fix from the title. Thermal noise is Gaussian, therefore the overall PFB test should be done in Gaussian noise, but the title suggests the other way around. Unrelated to the fix: I was saying that I implemented the same code in Matalb in case you would like to add it to the repository.

Best, XB

On Mon, Sep 21, 2020 at 10:51 AM Richard Elkins notifications@github.com wrote:

@xbosch https://github.com/xbosch It was simple to fix.

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-- Se'n va la primavera. Ploren les aus i son llàgrimes els ulls dels peixos.

Matsuo Bashö

[texadactyl]

@xbosch Yes, Danny would be interested as he already inidcated. I didn't mean to discourage you. Feel free to open a PR with your MATLAB source code added.

[telegraphic]

@xbosch yes still v. happy to add MATLAB code!