Hi Meng:
It is a compressive sensing method. Which serves as reconstruct signal from
indeterminacy sensing data:
Y = Phi * x + n
Where Phi is a N*M matrix with N much less than M.
Sorry for my English.
:)
Liu benyuan
在 2012-11-28，15:13，xinfan meng <[email protected]> 写道：
> You can first take a look at this page:
> http://scikit-learn.org/stable/developers/index.html .
>
> As to the model, is it a classification / clustering / factorization
> algorithm or something?
>
>
> On Wed, Nov 28, 2012 at 3:08 PM, <[email protected]> wrote:
>> Dear scikit-learn community:
>>
>> Block Sparse Bayesian Learning is a powerful CS algorithm for recovering
>> block sparse signals with structures, and shows the additional benefits of
>> reconstruct non-sparse signals, see Dr. zhilin zhang's websites:
>> http://dsp.ucsd.edu/~zhilin/BSBL.html
>>
>> I currently implement the BSBL-BO algorithm by Zhang and a fast version of
>> BSBL algorithm recently proposed by us, called BSBL-FM, in python. Plus many
>> demos using these two codes. Does scikit-learn community welcome such type
>> of code ? what is the procedure to submit the code in the mainstream of
>> scikit learn?
>>
>> Thanks for the great project!
>>
>> Liu benyuan
>>
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>
>
>
> --
> Best Wishes
> --------------------------------------------
> Meng Xinfan（蒙新泛）
> Institute of Computational Linguistics
> Department of Computer Science & Technology
> School of Electronic Engineering & Computer Science
> Peking University
> Beijing, 100871
> China
> ------------------------------------------------------------------------------
> Keep yourself connected to Go Parallel:
> INSIGHTS What's next for parallel hardware, programming and related areas?
> Interviews and blogs by thought leaders keep you ahead of the curve.
> http://goparallel.sourceforge.net
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