Assume that A is a
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Numerical Analysis
- 3 Find the dominant eigenvalue, 2,, and its corresponding eigenvector, v, of matrix A using the power method. Use v0) = (1 0 1)" and stop the iteration until | m-m, < 0.0005. Then, find the smallest eigenvalue, â,, and its corresponding eigenvector, v, of matrix A by using the shifted power method for Q3 (a)-(d). 161 Eigenvalues (2 1 0) A = 1 2 1 1 2 1 -1 (а). (b). A = -2 4 -2 0 1 -1 -1 0 -2 1 (c). A = -1 4 (d). A = -2 2 2 -2 3 II 2.arrow_forward0, 1, 1, 3, 5, 11,. A string of numbers starting with the numbers 0 and 1 is given above. For k> = 3, the previous two terms in the series The relation with the term can be expressed as ak=ak-1+2*ak-2 Using the eigenvalue vectors of the matrix A, calculate the 20th term of the array.arrow_forwardFind the first 3 iterations obtained by the power method for the 3 x 3 matrix 2 1 1 1 2 1 1 1 2 A= Compute the dominant eigenvector and eigenvalue of A, using=(-1 2 ).arrow_forward
- 4 Find all eigenvectors of the the matrix A = 2 3 (a) ; (b) ; (c) ; (d) ; C O b a d.arrow_forwardApply the power method anyway with th e given initial vector x0, performing eight iterations in each case. Compute the exact eigenvalues and eigenvectors and explain what is happening.arrow_forwardApply the inverse power method to approximate, for the matrix A , the eigenvalue that is smallest in magnitude. Use the given initial vector x0, k iterations, and three-decimal-place accuracyarrow_forward
- Find the eigenvalues and eigenvectors for the coefficient matrix.arrow_forward(d) cation. [11] =2 Write out eigendecomposition of A and verify it with the matrix multipli- m.arrow_forwardUse the power method to approximate the dominant eigenvalue and eigenvector of A. Use th e given initial vector x0 , th e specified number of iterations k, and three-decimal-place accuracy.arrow_forward
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