True. Matrices A and AT have the same characteristic polynomial, because det(AT — 11) = det(A — RI)T = det(A — RI), by the determinant transpose propefiY. False. Counterexample: Let A be the 5 x 5 identity If there is a basis B such that [TIB is diagonal, then A is similar to a diagonal matrix, by the second paragraph following Example 3.
Analogously a nonzero null vector y^* must exist such that y^* * A = lambda*y^*, and is called a left eigenvector. Def: If S is nonsingular, and B = S*A*inv (S), then S is called a similarity transformation, and A and B are called similar matrices.
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(i) Similar matrices have the same minimum and characteristic polynomials. In particular, similar matrices have the same eigenvalues. (Theorem 5.2.2 and Exercise 7 of section 5.5) Having reviewed these facts from Chapter 5, let us consider some easy examples to gain some experience with and appreciation for the theory we have just reviewed.

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  • 2 days ago · Matrices with same distinct eigenvalues are similar This is a problem from the entrance examination of the M.Math course of the Indian Statistical Institute held in 2020 which asks us to show that two matrices are similar.
  • If there exists a transposed matrix A T that satifies the eigenvalue equation, that is, if A T x = λx, then λx T = (λx) T = (A T x) T = x T A, or x T A = λx T. The last equation is similar to the eigenvalue equation but instead of the column vector x it contains its transposed vector, the row vector x T, which stands on the left side of the ...

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For example, →x ′ =A→x has the general solution. →x =c1[1 0]e3t +c2[0 1]e3t. 🔗. Let us restate the theorem about real eigenvalues. In the following theorem we will repeat eigenvalues according to (algebraic) multiplicity. So for the matrix A above, we would say that it has eigenvalues 3 and 3. 🔗.

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  • Suppose A;B are two similar matrices. Then, A and B have same eigenvalues. Proof. Write A = P 1BP:Then j I Aj= j I P 1BPj= j (P 1P) P 1BPj= jP 1( I B)Pj = jP 1jj I BjjPj= jPj1j I BjjPj= j I Bj So, A and B has same characteristic polynomials. So, they have same eigenvalues. The proof is complete. Satya Mandal, KU Eigenvalues and Eigenvectors x5 ...
  • If there exists a transposed matrix A T that satifies the eigenvalue equation, that is, if A T x = λx, then λx T = (λx) T = (A T x) T = x T A, or x T A = λx T. The last equation is similar to the eigenvalue equation but instead of the column vector x it contains its transposed vector, the row vector x T, which stands on the left side of the ...

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Adding and Subtracting Matrices. You can add or subtract matrices if each matrix has the same dimensions (in other words, each one needs to have exactly the same number of columns and rows). To add or subtract matrices , you just add or subtract the corresponding entries (the entries or numbers that are in the same spot).

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matrix A. So, both A and B are similar to A, and therefore A is similar to B. However, if two matrices have the same repeated eigenvalues they may not be distinct. For example, the zero matrix 1’O 0 0 has the repeated eigenvalue 0, but is only similar to itself. On the other hand the matrix (0 1 0

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May 02, 2009 · Similar matrices have the same characteristic polynomial and the same eigenvalues. Proof. If Q is nonsingular, then det( Q -1 ) det( Q ) = 1 , and the characteristic polynomials of A and Q -1 A Q are equal for all values of the independent variable:

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matrix A. So, both A and B are similar to A, and therefore A is similar to B. However, if two matrices have the same repeated eigenvalues they may not be distinct. For example, the zero matrix 1’O 0 0 has the repeated eigenvalue 0, but is only similar to itself. On the other hand the matrix (0 1 0

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Assuming that A and A-1 have the same eigenvectors, show that the eigenvalues of A-1 must be the reciprocals of the eigenvalues of A (i.e., 1/λ). Use the fact that A-1 (Au) = u-I have no idea how to do this, but thank you so much in advance!

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