Hi Kartik - Thanks for getting involved! There actually already was an HTML-based GRC on the ideas list, so I combined the new one you created with the existing one. I also made some minor edits to your Stastical Toolbox idea, and added my name as a Mentor.
Cheers, Ben On Thu, Feb 9, 2017 at 5:31 AM, Kartik Patel <[email protected]> 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 [email protected] 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 [email protected] >> 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 [email protected] >> 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 [email protected] >> 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 [email protected] 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 >> >> >> >> _______________________________________________ >> >> Discuss-gnuradio mailing list >> >> [email protected] >> >> https://lists.gnu.org/mailman/listinfo/discuss-gnuradio >> >> >> >> >> _______________________________________________ Discuss-gnuradio mailing >> list [email protected] >> https://lists.gnu.org/mailman/listinfo/discuss-gnuradio >> >> >> >> >> > _______________________________________________ > Discuss-gnuradio mailing list > [email protected] > https://lists.gnu.org/mailman/listinfo/discuss-gnuradio > >
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