Owning Palette: Linear Algebra VIs
Requires: Full Development System
Finds the eigenvalues and right eigenvectors of the square Input Matrix. Wire data to the Input Matrix input to determine the polymorphic instance to use or manually select the instance.
Use the pull-down menu to select an instance of this VI.
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Input Matrix is an n-by-n square, real matrix, where n is the number of rows and columns of Input Matrix. | ||||
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matrix type is the type of Input Matrix. A symmetric matrix needs less computation than an unsymmetrical matrix. A real, symmetric matrix always has real eigenvectors and eigenvalues.
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output option determines whether the VI computes Eigenvectors.
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Eigenvalues is a complex vector of n elements, which contains all of the computed eigenvalues of the Input Matrix. The Input Matrix could have complex eigenvalues if it is not symmetric. | ||||
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Eigenvectors is an n-by-n complex matrix containing all of the computed Eigenvectors of the Input Matrix. The ith column of Eigenvectors is the eigenvector corresponding to the ith component of the vector, Eigenvalues. Each eigenvector is normalized so that its Euclidean norm equals 1. The Input Matrix could have complex Eigenvectors if it is not symmetric. If output option is set to eigenvalues, the VI returns Eigenvectors as an empty array. |
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error returns any error or warning from the VI. You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster. |
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Input Matrix must be an n-by-n square, complex matrix, where n is the number of rows and columns of Input Matrix. | ||||
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matrix type is the type of Input Matrix. A symmetric matrix needs less computation than an unsymmetrical matrix. A Hermitian matrix always has real eigenvalues.
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output option determines whether the VI computes Eigenvectors.
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Eigenvalues is a complex vector of n elements, which contains all of the computed eigenvalues of the Input Matrix. The Input Matrix could have complex eigenvalues if it is not Hermitian. | ||||
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Eigenvectors is an n-by-n complex matrix containing all of the computed Eigenvectors of the Input Matrix. The ith column of Eigenvectors is the eigenvector corresponding to the ith component of the vector, Eigenvalues. Each eigenvector is normalized so that its Euclidean norm equals 1. If output option is set to eigenvalues, the VI returns Eigenvectors as an empty array. |
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error returns any error or warning from the VI. You can wire error to the Error Cluster From Error Code VI to convert the error code or warning into an error cluster. |
The eigenvalue problem is to determine the nontrivial solutions to the equation:
AX = 
X
where A is an n-by-n Input Matrix, X is a vector with n elements, and is a scalar. The n values of that satisfy the equation are the Eigenvalues of A and the corresponding values of X are the right Eigenvectors of A. A real, symmetric matrix always has real eigenvalues and eigenvectors. This VI returns the real eigenvalues in ascending order if the Input Matrix is a real symmetric matrix.
The eigenvalue problem is to determine the nontrivial solutions for the equation:
AX = X
where A represents an n-by-n Input Matrix, X represents a vector with n elements, and is a scalar. The n values of that satisfy the equation are the Eigenvalues of A and the corresponding values of X are the right Eigenvectors of A. A Hermitian matrix always has real eigenvalues. This VI returns the real eigenvalues in ascending order if the Input Matrix is a Hermitian matrix.
Refer to the following VIs for examples of using the Eigenvalues and Vectors VI:
Open example Find related examples
Open example Find related examples