Re: [Discuss-gnuradio] Google Summer of Code -- Ideas List!

[Martin Braun]

Please add some specifics and examples of what this should exactly do.
The project is too vague still to qualify for the ideas list.

Today, EOB, I'll review the list and make sure only fully fleshed-out
ideas are still on the list.

-- M

On 02/09/2017 02:31 AM, Kartik Patel wrote:
> Hello everyone,
> 
> The two of the ideas (1. statistical toolbox, 2. HTML based GRC) have
> been added in the GSoC Idea wiki page. 
> 
> Please review it and suggest any updates on /wiki/.
> 
> Thank you.
> 
> Regards,
> Kartik Patel
> 
> 
> 
> On Tue, Feb 7, 2017 8:24 PM, Marcus Müller address@hidden
> <mailto:address@hidden> wrote:
> 
>     __
> 
>     Hi Kartik,
> 
>     ha! Sorry for mixing this up. Yes, in that case, you'd be the GSoC
>     participant, not the mentor :)
> 
>     I've pinged the right people. Hopefully we can get your account going.
> 
>     Best regards,
> 
>     Marcus
> 
> 
>     On 02/06/2017 08:55 PM, Kartik Patel wrote:
>>     Hi Marcus,
>>
>>     I was interested in implementing this myself. Sorry for not
>>     clarifying. It would be my first time contributing a whole new
>>     feature to GNU Radio. I believe, the mentoring should be from
>>     someone who is more frequent contributor? If someone is interested
>>     in being the mentor to the project, it would be great.
>>
>>     I can add to wiki, but I don't have account on redmine. It is
>>     waiting to be approved from Admin for a long time.
>>
>>     Regards,
>>     Kartik Patel
>>
>>
>>
>>     On Tue, Feb 7, 2017 1:19 AM, Marcus Müller
>>     address@hidden <mailto:address@hidden> wrote:
>>
>>         Hi Kartik,
>>
>>         sorry, we've all been pretty busy over the Weekend – FOSDEM
>>         and stuff.
>>
>>         So, I personally think this is a pretty great idea that you
>>         should definitely put on the GNU Radio wiki page for GSoC
>>         ideas – if someone has a great idea how to improve what you're
>>         proposing, it's a wiki for a reason – so frankly, go for it.
>>         Notice that it'd be awesome if you putting this on the page
>>         also meant that you'd agree to at least partially mentor the
>>         student that picks that topic!
>>
>>         Best
>>
>>
>>         On 02/06/2017 08:26 PM, Kartik Patel wrote:
>>>         Hello all,
>>>
>>>         Any discussion over statistical toolbox?
>>>
>>>         Thank you.
>>>
>>>         Regards,
>>>         Kartik Patel
>>>
>>>
>>>
>>>         On Wed, Feb 1, 2017 1:32 AM, Kartik Patel
>>>         address@hidden <mailto:address@hidden>
>>>         wrote:
>>>
>>>             Hi Marcus,
>>>
>>>             Sorry for replying late. I was travelling.
>>>
>>>             My point is we can have a statistical module for GNU
>>>             Radio. Although Scipy has extensive library available, we
>>>             can have it's wrappers for GNU Radio. We can use those
>>>             wrappers in GRC. Basically, all major statistical
>>>             analysis can be done at GRC level instead of going to the
>>>             python/c++ backend.
>>>
>>>             There are some fundamental statistical tools (can be
>>>             extended with suggestions from community): 1. generation
>>>             of RV, 2. various distributions and distribution fitting,
>>>             3. regressions 4. hypothesis testing (including
>>>             non-parametric testing which basically check whether
>>>             current samples matches a particular distribution or not)
>>>             5. parameter estimations. We will need various
>>>             distributions/functions from Scipy.
>>>
>>>             So, consider a scenario where we have a block of "random
>>>             variable generators" which will get input from a block
>>>             called "distribution" which will specify the distribution
>>>             as well as it's parameters.
>>>             There can be another block for "distribution fitting".
>>>             Which will take two inputs: vector of samples and input
>>>             from "distribution" block.
>>>             Consider a hypothesis testing scenario: Get a input
>>>             vector: Provide a condition of testing (like energy of
>>>             vector should be greater than some value).
>>>             Consider a testing mechanism where we test whether a
>>>             sample vector is taken from a distribution or not (aka
>>>             non-parametric goodness-of-fit based testing): It may
>>>             take input from a "distribution block" and set of
>>>             samples. and based on value of some "false alarm
>>>             probability", it will give the decision.
>>>
>>>             We can try to make these testing completely generic.
>>>             Like, you can write whole equation in textbox in GRC (may
>>>             be. need to see how can we do it). It's similar to some
>>>             blocks in Simulink (not sure exactly which one, but I
>>>             remember those).
>>>
>>>             Note1: the "distribution" block will provide a
>>>             distribution object. It may work internally, or
>>>             externally. That's debatable.
>>>             Note2: This is a idea. We can discuss on various
>>>             implementation approaches once the scope of project etc
>>>             are discussed.
>>>
>>>             Regards,
>>>             Kartik Patel
>>>
>>>
>>>
>>>             On Thu, Jan 26, 2017 11:51 PM, Marcus Müller
>>>             address@hidden
>>>             <mailto:address@hidden> wrote:
>>>
>>>                 Hi Kartik,
>>>
>>>                 I heartily agree with you, you need a lot of random
>>>                 variables, but the question is: in which shape?
>>>
>>>                 Do you need the noise source to produce more
>>>                 different types of amplitude distributions? Do you
>>>                 need those in the channel models?
>>>
>>>                 "Blocks for hypothesis testing" sounds pretty
>>>                 interesting. Can you flesh out that idea a little
>>>                 more? In my head, I'm not sure what a /hypothesis/ is
>>>                 here.
>>>
>>>                 Best regards,
>>>
>>>                 Marcus
>>>
>>>
>>>                 On 01/26/2017 05:24 PM, Kartik Patel wrote:
>>>>                 Hi Martin,
>>>>
>>>>                 Till now, based on my experience in communication
>>>>                 systems, I saw extensive need of probability and
>>>>                 random variables.
>>>>
>>>>                 So, now, if we are considering GNU Radio to be a
>>>>                 full-fledged communication systems simulator, I
>>>>                 think we can have wrappers of statistical analysis
>>>>                 functions of Scipy. We can have GRC blocks for the
>>>>                 same.
>>>>
>>>>                 So, for an example, for spectrum sensing
>>>>                 applications, instead of writing a code with Scipy
>>>>                 library, we can have some blocks for direct
>>>>                 hypothesis testing.
>>>>
>>>>                 Regards,
>>>>                 Kartik Patel
>>>>
>>>>
>>>>
>>>>                 On Thu, Jan 26, 2017 4:07 PM, Martin Braun
>>>>                 address@hidden
>>>>                 <mailto:address@hidden> wrote:
>>>>
>>>>                     On 01/26/2017 12:07 AM, Kartik Patel wrote:
>>>>
>>>>                     > Hi,
>>>>
>>>>                     >
>>>>
>>>>                     > I am not sure how relevant is this, but it's
>>>>                     worth a consideration.
>>>>
>>>>                     >
>>>>
>>>>                     > Can we have a probability and statistical
>>>>                     toolbox? It may include
>>>>
>>>>                     > various probabilistic distributions, their
>>>>                     random number generators,
>>>>
>>>>                     > their PDFs and CDFs. These are very much
>>>>                     useful in a communication
>>>>
>>>>                     > system analysis. (Example: middleton noise
>>>>                     etc. for simulations). Even
>>>>
>>>>                     > adding various statistical functions like
>>>>                     hypothesis testing,
>>>>
>>>>                     > regressions, distribution fitting etc. can be
>>>>                     added.
>>>>
>>>>
>>>>                     Sure, although scipy has pretty good ones
>>>>                     already. Can you elaborate on
>>>>
>>>>                     how this would be useful for GNU Radio specifically?
>>>>
>>>>
>>>>                     -- M
>>>>
>>>>
>>>>
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>>>>
>>>>
>>>>
>>>>
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>>
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