CS计算机代考程序代写 matlab [Content_Types].xml

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Implicit Methods In this livescript, you will learn how To solve initial value problems using implicit methods. The two implicit methods that we have covered in this course are the implicit Euler method x_{n+1}=x_{n}+\Delta t f(t_{n+1},x_{n+1}) and the Crank-Nicolson method x_{n+1}=x_{n}+\frac{\Delta t}{2}(f(t_{n},x_{n})+f(t_{n+1},x_{n+1})) To look at how to apply these, consider the initial value problem \frac{dx}{dt}=-x^2 with the initial condition x(0)=1 . Before we solve this we’ll again initialise out variables and define all the relevant parameters. dt = 0.01;
t = 0:dt:20;
x = zeros(1,length(t));
x(1) = 1; For the sake of brevity, we’ll consider the implicit Euler method, which gives the iterative formula x_{n+1}=x_{n}-\Delta t x_{n+1}^{2} However, we can see that there is a nonlinear dependence on x_{n+1} . Nevertheless, we can write this as the root finding problem with p=x_{n+1} f(p)=\Delta t p^{2}+p-x_{n}=0 To solve this we can apply the Newton-Raphson method to give p^{(i+1)}=p^{(i)}-\frac{f(p^{(i)})}{f'(p^{(i)})} The only issue is how we choose our initial guess for the Newton-Raphson method. Assuming that the solution is continuous, which is required for the Newton-Raphson method, then x_{n} will be somewhat close to the next iterate x_{n+1} . So, for the first iterate, we have the piece of code p = x(1);
i = 1;
f = dt*p^2+p-x(1);

while abs(f)>tol && itol && i