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from Complex Optimization of a Recurrent Neural Network by Travis Wiens
Shows how to use the complex method to optimize a black-box neural network model of a load-sensing h

W=params_to_W(P,N_in);
function W=params_to_W(P,N_in);
%W=params_to_W(P,N_in);
%decodes square W matrix from parameter vector

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%Copyright (c) 2009, Travis Wiens
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if nargin<2
	W=reshape(P,sqrt(numel(P)),[]);
else
	N=round(max(roots([1 -N_in -numel(P)])));
	W=zeros(N);
	W((N_in+1):end,:)=reshape(P,N-N_in,N);
end

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