## implementation help of Gaussian RBM in matlab

### subha (view profile)

on 23 Nov 2013
Latest activity Commented on by subha

on 28 Nov 2013

### Greg Heath (view profile)

First i would like to know how to make visible layer to zero mean and unit variance.I have seen in few example they followed below way.but i couldnot understand

subtracting the corresponding data with its mean and divide it by standard division, my data becomes NaN.

I am new to matlab and Neural networks.

```data= batchdata(:,:,batch);
mean_data=mean(data,1),data=bsxfun(data,mean_data);
std_data=std(data,[],1);
data=bsxfun(@rdivide,data,std_data);
```

i am not able to find the reason

can anybody help to clear this

Greg Heath

### Greg Heath (view profile)

on 23 Nov 2013

"subtracting the corresponding data with its mean and divide it by standard division, my data becomes NaN."

Did it ever occur to you to post that code?

## Products

### Greg Heath (view profile)

on 23 Nov 2013
```doc zscore
help zscore
```
```doc mapstd
help mapstd
```

Hope this helps.

• Thank you for formally accepting my answer*

Greg

subha

### subha (view profile)

on 23 Nov 2013

But i am sure mean zero and unit variance can be achieved in that way also.But i would like to know why it didn't work.What mistake i have done when i implement it.

thanks and regards subha

Greg Heath

### Greg Heath (view profile)

on 25 Nov 2013
``` [x, t ] = engine_dataset;
[ I N ] = size(x)   %  2  1199
[ O N ] = size(t)   %  2  1199```
``` z    = [ x; t];
muz  = mean(z')';
stdz = std(z')';
% [ muz stdz ] = [ 141.2  090.7
%                 1259.5  354.8
%                  754.2  548.7
%                  961.7  466.1 ]```
``` zn    = ( z - repmat(muz,1,N))./repmat(stdz,1,N);
muzn  = mean(zn')';
stdzn = std(zn')';
% [ muzn stdzn ] = [  -0.0000    1.0000
%                      0.0000    1.0000
%                     -0.0000    1.0000
%                     -0.0000    1.0000 ]```
subha

### subha (view profile)

on 28 Nov 2013

thanks.

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