a) suppose that the nxn matrix A has its n eigenvalues arranged
in decreasing order of absolute size, so that >
>...
.
each eigenvalue has its corresponding eigenvector, x1,x2,...,xn.
suppose we make some initial guess y(0) for an eigenvector.
suppose, too, that y(0) can be written in terms of the actual
eigenvectors in the form y(0)=alpha1.x1 +alpha2.x2
+...+alpha(n).x(n), where alpha1, alpha2, alpha(n) are constants.
by considering the "power method" type iteration y(k+1)=Ay(k) argue
that (see attached image)
b) from an nxn matrix A, with eigenvalues and eigenvectors in part a, show that inverse matrix A^-1 has the same eigenvectors as A, but that its eigenvalues are 1/lamda1, 1/lamda2,...,1/lamda(n). what will the power method do, if applied to this inverse matrix A^-1
c)the nxn matrix B is defined to be similar to nxn matrix A if B=P^(-1)AP. here P is a non-singular nxn matrix. show that B has the same eigenvalues as A.
a) suppose that the nxn matrix A has its n eigenvalues arranged in decreasing order of absolute size, so that >>....
(1 point) Suppose that the matrix A has the following eigenvalues and eigenvectors: A1 = 4 with = and [2] [i] Az = 3 with Ū2 = Write the solution to the linear system r' = Ar in the following forms. A. In eigenvalue/eigenvector form: t (10) -- + C2 e e B. In fundamental matrix form: (39) - g(t). C. As two equations: (write "c1" and "c2" for C and C2) X(t) = g(t) = Note: if you are...
True False a) For nxn A, A and AT can have different eigenvalues. b) The vector v 0 cannot be an eigenvector of A. c) If λ's an eigenvalue of A, then λ2 is an eigenvalue of A2. True False d) If A is invertible, then A is diagonalizable. e) If nxn A is singular, then Null(A) is an eigenspace of A. f) For nxn A, the product of the eigenvalues is the trace of A. True False g) If...
Suppose that the matrix A A has the following eigenvalues and
eigenvectors:
(1 point) Suppose that the matrix A has the following eigenvalues and eigenvectors: 2 = 2i with v1 = 2 - 5i and - 12 = -2i with v2 = (2+1) 2 + 5i Write the general real solution for the linear system r' = Ar, in the following forms: A. In eigenvalue/eigenvector form: 0 4 0 t MODE = C1 sin(2t) cos(2) 5 2 4 0 0...
(1 point) Suppose that the matrix A has the following eigenvalues and eigenvectors: 4 = 2 with vi = and |_ G 12 = -2 with v2 = Write the solution to the linear system r' = Ar in the following forms. A. In eigenvalue/eigenvector form: x(t) (50) = C1 + C2 e e B. In fundamental matrix form: (MCO) = I: C. As two equations: (write "c1" and "c2" for C1 and c2) x(t) = yt) =
5. The following matrix B has known eigenvalues λ1-1 and λ2-6. 10a-1 B-0b-23 c30 0 Where a, b and c real numbers and vis the eigenvector associated with the eigenvalue A1. e. Determine as many of a, b, and c as you can. f.Determine the third eigenvalue, if possible. g.Determine the second and third eigenvectors, if possible.
0 -2 - The matrix A -11 2 2 -1 has eigenvalues 5 X = 3, A2 = 2, 13 = 1 Find a basis B = {V1, V2, v3} for R3 consisting of eigenvectors of A. Give the corresponding eigenvalue for each eigenvector vi.
(1 point) Suppose that the matrix A has repeated eigenvalue with the following eigenvector and generalized eigenvector: X= -4 with eigenvector v = and generalized eigenvector ū= [] (-1) Write the solution to the linear system r' = Ar in the following forms. A. In eigenvalue/eigenvector form: t t [CO] = C1 + C2 + I g(t). e . - 1 B. In fundamental matrix form: [CO] C. As two equations: (write "c1" and "c2" for 1 and 2) X(t)...
Consider the matrix A= 2 -2 0 1 -1 0 2 -4 1 which has eigenvalues 1 = 1,1,0. a) Show that the characteristic polynomial of A is p(a) = -2(1 - 1) 2. b) Compute the eigenvectors of A. c) show that what you found are indeed eigenvalue- eigenvector pairs for A.
NEED HELP WITH PROBLEM 1 AND 2 OF THIS LAB. I NEED TO PUT IT
INTO PYTHON CODE! THANK YOU!
LAB 9 - ITERATIVE METHODS FOR EIGENVALUES AND MARKOV CHAINS 1. POWER ITERATION The power method is designed to find the dominant' eigenvalue and corresponding eigen- vector for an n x n matrix A. The dominant eigenvalue is the largest in absolute value. This means if a 4 x 4 matrix has eigenvalues -4, 3, 2,-1 then the power method...
True or False?
1. If σ is a singular value of a matrix A, then σ is an eigenvalue of ATA Answer: 2. Every matrix has the same singular values as its transpose Answer: 3. A matrix has a pseudo-inverse if and only if it is not invertible. Answer: 4. If matrix A has rank k, then A has k singular values Answer:_ 5. Every matrix has a singular value decomposit ion Answer:_ 6. Every matrix has a unique singular...