Jacobi Iteration Homework: Solving System of Equations

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In summary, the conversation discusses solving a system of equations using Jacobi iteration and determining the necessary number of iterations to reach a desired solution accuracy. The conversation also mentions calculating error bounds for each iteration and using an expression to find the number of iterations needed to reach a specific accuracy.
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gtfitzpatrick
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Homework Statement



consider the systems of equations
2x1 - x2 = 1
-31 + 4x2 =11

a) determine the ixact solution?

b)apply jacobi iteration.Does the matrix C satisfy the required condition?

c)starting with x(0) =( [tex]\stackrel{1}{1}[/tex] ) calculate x(1) and x(2) and the prior error bound for x(2)

d)how many iterations will suffice to get within 0.001 of the solution?

a) grand 3 and 5
b) it clearly satisfies the condition as off diagonals < diagonals
c) so did it out got
x(0) = ( [tex]\stackrel{1}{14/4}[/tex] )

x(1) = ( [tex]\stackrel{18/8}{14/4}[/tex] )

x(2) = ( [tex]\stackrel{18/8}{71/16}[/tex] )

but now I am not sure what is meant by prior error bound, compare with the actual error?

d) do i just keep doing it out till i get within .001? (aghhhhh)
 
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but now I am not sure what is meant by prior error bound, compare with the actual error?

It's the error estimate that can be obtained before the actual iteration's calculus. There's an expression for it in terms of the matrixes.

do i just keep doing it out till i get within .001?

No. You use the expression for the a priori error (it depends on n) to find n.
 

1. What is Jacobi Iteration?

Jacobi Iteration is an iterative method used to solve a system of linear equations. It involves breaking down the original system into smaller subsystems and repeatedly solving them until a solution for the entire system is obtained.

2. How does Jacobi Iteration work?

In Jacobi Iteration, the original system of equations is first expressed in the form of x = Bx + c, where B is a matrix of coefficients and c is a vector. Then, the initial guess for the solution is plugged into the equation to get a new approximation for x. This process is repeated until the approximations converge to the actual solution.

3. What are the advantages of using Jacobi Iteration?

Jacobi Iteration is a simple and easy-to-implement method for solving systems of linear equations. It can handle large systems of equations and is particularly useful for sparse matrices. Additionally, it can be easily parallelized, making it efficient for computation on multiple processors.

4. What are the limitations of Jacobi Iteration?

One major limitation of Jacobi Iteration is that it is not guaranteed to converge for all systems of equations. In some cases, it may take a large number of iterations to obtain an accurate solution. It also requires the initial guess to be close to the actual solution for faster convergence. Another limitation is that it may not work well for systems with complex eigenvalues.

5. How can Jacobi Iteration be applied in real-world problems?

Jacobi Iteration can be used in a variety of real-world problems, such as solving systems of differential equations in physics and engineering, optimizing financial models, and image processing in computer vision. It is also commonly used in solving large systems of equations in finite element analysis and computational fluid dynamics.

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