model3.m

Incorporating Prior Knowledge in Cubic Spline Approximation - Application to the Identification of R

%Start
clear all
addpath '.\Libary'
load data_conc
load data_conc_big
cold = c;

M1 = zeros(3,10);
M2 = zeros(3,10);
cycnum = 100;
erv = [0 0.05 0.10];
knot{1} = [0 0.5 1 2];
knot{2} = [0 1 2];
knot{3} = [0 2];

%31
tin = t31;
cin = c31;
for I2=1:3,
 if I2==1,
  for I4=1:3,
   [P1,P2] = spline_no(cold,tin,cin,erv(I2),0,knot{I4},1);
   M1(I4,0+1) = mean(P1);
   M2(I4,0+1) = mean(P2);
  end
 else
  for I3=0:1,
   for I4=1:3,
    [P1,P2] = spline_no(cold,tin,cin,erv(I2),I3,knot{I4},cycnum);
    M1(I4,0+I2*2-2+I3) = mean(P1);
    M2(I4,0+I2*2-2+I3) = mean(P2);
   end
  end
 end
end    

%12
tin = t12;
cin = c12;
for I2=1:3,
 if I2==1,
  for I4=1:3,
   [P1,P2] = spline_no(cold,tin,cin,erv(I2),0,knot{I4},1);
   M1(I4,0+6) = mean(P1);
   M2(I4,0+6) = mean(P2);
  end
 else
  for I3=0:1,
   for I4=1:3,
    [P1,P2] = spline_no(cold,tin,cin,erv(I2),I3,knot{I4},cycnum);
    M1(I4,5+I2*2-2+I3) = mean(P1);
    M2(I4,5+I2*2-2+I3) = mean(P2);
   end
  end
 end
end    

%End
M1
M2
save model3 M1 M2
rmpath '.\Libary'