Re: neural networks normalization

Hi Ruben
Thanks for your question.
Please explain where I have to use "On the other hand, you can create your MLP and you can do later nn.inputs{1}.processFcns={} and nn.outputs{1}.processFcns={}." in the newff command or after training the network.
Regards
Afaq





"Ruben Saborido Infantes" <ruben.saborido.infantes@gmail.com> wrote in message <ha4pj0$k5b$1@fred.mathworks.com>...
> Hello Berriah.
>
> If you want to avoid that MATLAB normalize your data, you must create the MLP by the next way:
>
> nn=newff(inputs, targets, {number_of_neurons_hidden_layer},{'transfer_function_for_neurons_of_hidden_layer', 'transfer_function_for_output_layer's neurons'},'trainlm','learngdm', 'mse', {}, {}, 'dividerand');
>
> The params {} is for IPF and OPF.
>
> On the other hand, you can create your MLP and you can do later nn.inputs{1}.processFcns={} and nn.outputs{1}.processFcns={}.
>
>
> It's works, I promise to you ;-)
>
> See you!
>
> P.D.: Sorry my English, I'm Spanish.
> Rub?n.
>
> "Said Berriah" <sberri@hotmail.com> wrote in message <gvou01$44k$1@fred.mathworks.com>...
> > In the 2008b version the normalization is by default performed when we create a neural net with a function like: newff.
> >
> > Is there a way to create a neural net (back prop) without any normalization by default.
> >
> > Thanks.