MATLAB: How i can save the output of hidden layer of neural network

Deep Learning Toolboximage compressionneural network

after i complete my program,i want to save the output,weight and bias of hidden layer of neural network, can any one help me to do this? thanks

Best Answer

close all, clear all, clc, plt=0;
 delete h.mat
 delete LW.mat
 delete b2.mat
 delete tsettings.mat
 [ x, t ] = simplefit_dataset;
 net   = fitnet;
 rng(4151941) 
 [ net tr y0 ] = train( net, x, t);
 plt=plt+1,figure(plt)                                   % figure 1
 hold on
 plot(x,t,'b--','LineWidth',2)
 plot(x,y0,'r.','LineWidth',2)
 legend('TARGET','NN OUTPUT')
 xlabel('INPUT')
 ylabel('TARGETAND NN OUTPUT')
 title('SIMPLEFIT DATASET')
%Create tsettings, h, LW, b2
 [xn xsettings] = mapminmax(x);
 [tn tsettings]  = mapminmax(t);     % SAVE tsettings
 b1  = cell2mat(net.b(1))
 IW = cell2mat(net.IW)
 [ I N ]  = size(xn)
 B1  = b1*ones(1,N);
 % B1 = repmat(b,1,N);             % Alternate
 h    = tanh(B1+IW*xn);             % SAVE h
 LW = cell2mat(net.LW)           % SAVE LW
 b2 = cell2mat(net.b(2))            % SAVE b2
 clc
 whos h LW b2 tsettings
 dir
% save FILENAME ... is the command form of the syntax
% for convenient  saving from the command line.  With 
% command syntax, you do not need to  enclose strings in 
% single quotation marks.  Separate inputs with spaces
% instead of commas.  Do not use command syntax if 
% inputs such as FILENAME are variables.
 save h
 save LW
 save b2
 save tsettings
 dir
 whos N h LW b2 tsettings
 disp('BEFORE CLEARING SAVED HIDDEN VARIABLES')
 disp('ENTER TO CONTINUE')
 pause
 dir
 clear     h LW b2 tsettings
 whos N h LW b2 tsettings
 disp('AFTER CLEARING SAVED HIDDEN VARIABLES')
 disp('ENTER TO CONTINUE')
 pause
 load      h.mat
 load      LW b2 tsettings
 whos N h LW b2 tsettings
 disp('AFTER RELOADING SAVED HIDDEN VARIABLES')
 disp('ENTER TO CONTINUE')
 pause
 yn = b2 + LW*h;
 y  =  mapminmax('reverse',yn,tsettings);
 reloadingerror = max(abs(y-y0))
 break
% Hope this helps
Thank you for formally accepting my answer
Greg
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