function a = simff_snn (X, net, data)%SIMFF_SNN Simulate a feed forward neural network.%%  Syntax%%    y = simff_snn(net, P)%%  Description%%   SIMFF_SNN takes%      net   -  a net_struct with the neural network%      P     -  [N0 x MU] matrix with inputs%   and returns %      y     -  [NL x MU] matrix with outputs%%   (N0 = #inputs; NL = #outputs; MU = #patterns)%%  Example%%   MU = 60;%   data.P = 2*pi*rand(1,MU);%   data.T = sin(data.P) + 0.1*randn(size(data.P));%   net = net_struct_snn([1 8 1], {'tansigtf_snn', 'lintf_snn'}, 'trainlm_snn');%   [net, tr_info] = train_snn(net, data)%%   P = [0:0.1:6]; %   y = simff_snn(net, P)%%%  See also%%   NET_STRUCT_SNN, TRAIN_SNN%%%  Additional syntax (also supported; not documented)%%    y = simff_snn(net, data)%    y = simff_snn(X, net, P)%    y = simff_snn(X, net, data)%if (nargin == 2)           % simff_snn(net, P) or simff_snn(net,data)   if (isfield(net, 'P'))  % simff_snn(net, data)      a = sim_all(X, net.P);   else                    % simff_snn(net, P)      a = sim_all(X, net);    end   return;elseif (nargin == 3)       % simff_snn(X, net, P) or simff_snn(X, net, data)   net = setx_snn(net,X);   if (isfield(data, 'P')) % simff_snn(X, net, data)      a = sim_all(net, data.P);   else                    % simff_snn(X, net, P)      a = sim_all(net, data);    endelse   error('Incorrect number of input arguments');end%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%function a = sim_all(net, P)q = size(P,2);a = feval(net.transferFcn{1}, net.weights{1}*P ...                              + repmat(net.biases{1}, 1, q));if (net.numLayers > 1)   for i = 2:net.numLayers      a = feval(net.transferFcn{i}, net.weights{i}*a ...                              + repmat(net.biases{i},1, q));   end   return;end%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%