??? Error using ==> TS1>feed_forward_signalsToo many input arguments.Error in ==> TS1>Run_Neural_Net_Regression at 144feed_forward_signals(hidden_input_wts,input,hidden,hidden_bias,25,8,0)Error in ==> TS1 at 100Run_Neural_Net_Regression(hidden_input_wts,input,hidden,hidden_bias,hidden_output_wts,... Error in ==> Neural_network>Calculate_Callback at 1162data = TS1();
Code
scale_inputs(input,0,1,25,max_input,min_input);Run_Neural_Net_Regression(hidden_input_wts,input,hidden,hidden_bias,hidden_output_wts,... output,output_bias);unscale_targets(output,0,1,1,max_target,min_target);% handles.TS=output(1);
% guidata(hObject, handles)
data.TS = 300;% setappdata(fig_handle, 'metricdata', data);
% set(handles.TS, 'String', data.TS);
x=100;function scale_inputs(input,minimum,maximum,size,max_input,min_input)for i = 1:size delta = (maximum-minimum)/(max_input(i)- min_input(i)); input(i) = minimum - delta*min_input(i)+ delta*input(i);endendfunction unscale_targets(output,minimum,maximum,size,max_target,min_target)for i = 1:size delta = (maximum-minimum)/(max_target(i)-min_target(i)); output(i) = (output(i) - minimum + delta*min_target(i))/delta;endendfunction feed_forward_signals(MAT_INOUT,V_IN,V_OUT,V_BIAS,size1,size2) %%%,layer)
for row = 1:size2 V_OUT(row)=0; for col = 1:size1 V_OUT(row)=V_OUT(row)+MAT_INOUT(row,col)*V_IN(col); end V_OUT(row)=V_OUT(row)+V_BIAS(row); %if layer==0
% V_OUT(row) = exp(V_OUT(row));
%end
% if layer==1
% V_OUT(row) = exp(V_OUT(row));
% end
endendfunction Run_Neural_Net_Regression(hidden_input_wts,input,hidden,hidden_bias,hidden_output_wts,... output,output_bias)feed_forward_signals(hidden_input_wts,input,hidden,hidden_bias,25,8,0)feed_forward_signals(hidden_output_wts,hidden,output,output_bias,8,1,1)endend
Best Answer