elm.rar_ELM

A=[ 15 200 26.32 15 350 26.97 15 500 26.97 15 650 27.63 16 450 26.97 16 700 26.97 16 900 27.63 16 1100 27.63 17 300 26.32 17 600 26.97 17 800 26.97 17 1200 26.97 18 150 25.004 18 400 26.32 18 750 26.97 18 1300 26.97 19 250 25.66 19 550 26.97 19 850 26.97 19 1000 26.97 20 200 25.004 20 450 26.32 20 700 26.97 20 1050 26.97 21 220 25.66 21 530 26.32 21 740 26.97 21 1120 26.97 22 170 25.004 22 460 26.32 22 820 26.97 22 1250 26.97 23 310 25.66 23 770 26.32 23 930 26.32 23 1300 26.32 24 180 25.004 24 390 25.66 24 680 26.32 24 990 26.32 25 200 25.004 25 440 25.66 25 710 26.32 25 1000 26.32 26 340 25.004 26 760 26.32 26 980 26.32 26 1240 26.32 27 160 24.34 27 420 25.66 27 800 25.66 27 1100 26.32 28 170 24.34 28 500 25.66 28 900 25.66 28 1250 25.66 29 250 25.66 29 670 25.66 29 890 25.66 29 1115 25.66 30 125 23.02 30 400 25.004 30 800 25.66 30 1050 25.66 31 225 24.34 31 550 25.006 31 770 25.66 31 1250 25.66 32 150 23.03 32 430 25.006 32 830 25.66 32 998 25.66 33 300 24.34 33 555 25.006 33 790 25.006 33 1175 25.006 34 180 23.68 34 490 25.006 34 670 25.006 34 1200 25.006 35 300 23.68 35 530 24.34 35 891 25.006 35 1300 25.006 36 175 23.03 36 450 24.34 36 734 25.006 36 1025 23.03 37 200 24.34 37 510 25.006 37 920 25.006 37 1130 23.03 38 175 23.68 38 375 24.34 38 680 24.34 38 1000 22.37 39 150 23.68 39 400 24.34 39 860 24.34 39 1075 22.37 40 176 23.68 40 350 24.34 40 790 24.34 40 1000 25.4 ]; %first 500 data used as training samples x = [1:104,1:3]; %column 1 to 3 of first 500 data T = [1:104,3]; %column 4 of first 500 data C = 2^20; %C is user define parameter, can be from 2^-n to 2^m L = 1000; %number of hidden neuron, user define N = 2; %number of input dimension I = eye(L,L); %create a L x L indentity matrix a = rand(L,N)*2 - 1; %randamly generate a matrix, dimension is L x N b = rand(1,L)*2 - 1; %randamly generate b matrix, dimension is 1 x L %first 500 data used as training samples z = A(104:end,1:3); %column 1 to 3 yperfect = A(104:end,3); h = (z, a, b , 'sig'); G = (I/C + H'*H); yelm = h*(G^-1)*H'*T; %denomaize yelm and yperfect to original range yperfect = (yperfect*(302-60) + 60 + 302)/2; yelm = (yelm*(302-60) + 60 + 302)/2; err = mse([yperfect - yelm])^0.5; hold on; plot(yperfect, 'b'); plot(yelm, '--r'); title(err); legend('expected output', 'prediction of ELM'); toc