Write a MATLAB implementation that applies the classical fourth order RK method
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clc
clear
B=4;
f1=@(t,u,v)v;
f2=@(t,u,v)5*exp(-2*t)+2*exp(-(B+2)*t)+exp(-(B*t))+t-v*exp(-B*t)-u;
a=0; % intial point of t
b=1;% final point of t
n=20; % step legth
s=1;
y=zeros(1,n+1);
while(n<=160)
h=(b-a)/n; % number of intervals
t=a:h:b; % t runing from a to b
u(1)=1; % initial value of Q
v(1)=-1;% initial value of I
% Rk2 method for two variable
for i=1:n
k1=h*f1(t(i),u(i),v(i));
k2=h*f2(t(i),u(i),v(i));
l1=h*f1(t(i)+h,u(i)+k1,v(i)+k2);
l2=h*f2(t(i)+h,u(i)+k1,v(i)+k2);
u(i+1)=u(i)+(1/2)*(k1+l1);
v(i+1)=v(i)+(1/2)*(k2+l2);
end
for i=1:n+1
y(1,i)=exp(-2*t(i))+t(i);
end
err(s)=max(abs(u-y));
N(s)=n;
n=2*n;
s=s+1;
end
varNames = {'N','Relative Error'};
table(N',err','VariableNames',varNames)

I'm trying to make the code I wrote above similar to the solution in this question, but I failed, can you help?
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Modify the Runge-Kutta code supplied here according to your needs:
Alper Sahin
2021년 12월 27일
Alper Sahin
2021년 12월 27일
Alper Sahin
2021년 12월 27일
If your task were to solve 100 ODEs at a time, would you code the Runge-Kutta scheme as above by using 100 lines of code to evaluate the functions, 100 lines of code per Runge-Kutta coefficient k0,k1,k2,... and 100 lines of code to update the 100 functions ? Use arrays instead.
Take a look at the code I linked to on how to do this.
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