Matrix A is factored in the form PDP. Use the Diagonalization Theorem to find the eigenvalues of A and a basis for each eigenspace. 1 2 221 1 2 2 A= 13 1 =1 0-1 122 1-2 500 010 001 1 4 1 8 1 4 1 4 1 4 3 8 1 1 2 4 *** (Use a comma to separate vectors as needed.) OA. There is one distinct eigenvalue, A= A basis for the corresponding eigenspace is {}. B. In ascending order, the two distinct eigenvalues are X, 1 and 2-5. Bases for the corresponding eigenspaces are = OC. In ascending order, the three distinct eigenvalues are A₁, A₂, and A 2 0 -2 and 2 , respectively. Bases for the corresponding eigenspaces are.. and , respectively. 4
Matrix A is factored in the form PDP. Use the Diagonalization Theorem to find the eigenvalues of A and a basis for each eigenspace. 1 2 221 1 2 2 A= 13 1 =1 0-1 122 1-2 500 010 001 1 4 1 8 1 4 1 4 1 4 3 8 1 1 2 4 *** (Use a comma to separate vectors as needed.) OA. There is one distinct eigenvalue, A= A basis for the corresponding eigenspace is {}. B. In ascending order, the two distinct eigenvalues are X, 1 and 2-5. Bases for the corresponding eigenspaces are = OC. In ascending order, the three distinct eigenvalues are A₁, A₂, and A 2 0 -2 and 2 , respectively. Bases for the corresponding eigenspaces are.. and , respectively. 4
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter10: Matrices
Section10.5: Eigenvalues And Eigenvectors
Problem 17E: In Exercises 16 and 17, each matrix has complex numbers as eigenvalues. Find eigenvalues and their...
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