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mcbonov
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Homework Statement
Let A be an invertible matrix.
show that if λ is an eigenvalue of A,
then 1/λ is an eigenvalue of A^-1
PLEASE HELP ME .
Thank you.
mcbonov said:Homework Statement
Let A be an invertible matrix.
show that if λ is an eigenvalue of A,
then 1/λ is an eigenvalue of A^-1
PLEASE HELP ME .
Thank you.
No, you can't say this. A is a matrix, but λ is a scalar. You can't subtract a scalar from a matrix. What you can say is this:mcbonov said:i tried Ax =λx
(Ax-λx)=0
(A-λ)x=0 since x is not a zero vector
Makes no sense, since A and λ are two completely different kinds of things.mcbonov said:A-λ=0 then A=λ
mcbonov said:THEN A^-1 = λ^-1
so (A^-1)x = (λ^-1)x
I basically don't know how to prove...
I don't think the above is near to correct answer.
that's the most I can do ...
how can i solve this problem??
Linear algebra is a branch of mathematics that deals with the study of linear equations and their relationships. It involves the use of matrices, vectors, and linear transformations to solve systems of linear equations and understand geometric concepts such as lines and planes.
An invertible matrix is a square matrix that has a unique solution for every system of linear equations that it represents. This means that it can be reversed or "inverted" to find the original values of the variables in the system of equations. An invertible matrix must have a non-zero determinant, meaning that its columns are linearly independent.
To determine if a matrix is invertible, you can calculate its determinant. If the determinant is non-zero, then the matrix is invertible. Additionally, you can use the Gaussian elimination method to transform the matrix into its reduced row echelon form. If all of the pivot elements are non-zero, then the matrix is invertible.
An eigenvalue of a matrix is a scalar value that represents a special type of transformation that occurs when the matrix is multiplied by a vector. This transformation is known as an eigenvector, and it represents the direction in which the vector is stretched or compressed by the matrix. The eigenvalues can be calculated by solving the characteristic equation of the matrix.
Eigenvalues are important in linear algebra because they provide information about the properties of a matrix and its corresponding linear transformation. They can be used to determine the stability of a system, find the equilibrium points of a system, and analyze the behavior of a system over time. Additionally, eigenvalues are used in many other areas of mathematics, such as differential equations and physics.