Kevin,

Adding on to what Fergal said..

 

Here is what we did.  We started with a fixed number of columns and no
topology.  In this situation we picked the n% most innervated columns as the
output of the SP.  Thus we were guaranteed to get the correct sparsity of
active columns.  With this setup we did a lot of other tests to verify that
the SP was forming good representations.

 

The tricky part is if you want to do this with topology and local learning
rules.   Is that your concern?

 

With topology we didn't try to guarantee the entire layer of cells will have
exactly n% active columns.  Exact numbers are not essential.  We tried
several different local learning rules, all of them produced about the right
level of sparsity.  We than ran the other tests to make sure that local
learning rules didn't cause the SP to form poor representations.  You won't
get exactly the same results with topology and without topology but my
recollection was we were able to come up with a set of local inhibition
rules that produced good results.

Jeff

 

From: nupic [mailto:[email protected]] On Behalf Of Fergal
Byrne
Sent: Tuesday, February 04, 2014 10:43 AM
To: NuPIC general mailing list.
Subject: Re: [nupic-discuss] Tests for spatial pooling

 

Hi Kevin,

 

If you're using no topology (and no local inhibition) then the fraction of
active columns (2% in NuPIC) is the only important factor. With topology,
you should choose winners relative to their neighbours. In either case, the
first test is to count the fraction of active columns. In the second case,
measure the average distance between active columns.

 

Regards,

 

Fergal Byrne

 

On Tue, Feb 4, 2014 at 6:05 PM, Kevin Martin <[email protected]>
wrote:

Hi,

I'm writing my own version of the CLA. I have not reached anywhere
significant and I have been playing with a very small number of columns
until now. I am starting by implementing a spatial pooler and spatial
pooling requires a large number of columns. So far it has been easy to
manually check if the synapses are distributed throughout the input, if the
winning columns are really sparse etc. But it is going to be impossible
when, say,I use 1000 columns. Have somebody used a test to check if the
spatial pooler outputs a sparse distribution? Any suggestions on how to
write a test?

Thanks,

Kevin Martin Jose


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-- 


Fergal Byrne, Brenter IT

 

http://inbits.com - Better Living through Thoughtful Technology

 

e:[email protected] t:+353 83 4214179

Formerly of Adnet [email protected] http://www.adnet.ie <http://www.adnet.ie/>


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