image thumbnail
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

P=W_to_param(W,N_in);
function P=W_to_param(W,N_in);
%P=W_to_param(W,N_in);
%encodes W in parameter vector

%
%Copyright (c) 2009, Travis Wiens
%All rights reserved.
%
%Redistribution and use in source and binary forms, with or without 
%modification, are permitted provided that the following conditions are 
%met:
%
%    * Redistributions of source code must retain the above copyright 
%      notice, this list of conditions and the following disclaimer.
%    * Redistributions in binary form must reproduce the above copyright 
%      notice, this list of conditions and the following disclaimer in 
%      the documentation and/or other materials provided with the distribution
%      
%THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 
%AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 
%IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 
%ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE 
%LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 
%CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 
%SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS 
%INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN 
%CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 
%ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 
%POSSIBILITY OF SUCH DAMAGE.
%
% If you would like to request that this software be licensed under a less
% restrictive license (i.e. for commercial closed-source use) please
% contact Travis at travis.mlfx@nutaksas.com

if nargin<2
	P=reshape(W,1,[]);
else
	P=reshape(W((N_in+1):end,:),1,[]);
end

Contact us at files@mathworks.com