Table Of Contents

Linear Algebra Nodes (G Dataflow)

Last Modified: December 4, 2016

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Performs the multiplication of two input matrices or an input matrix and an input vector.
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Transforms the eigenvectors of a balanced matrix to those of the original matrix.
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Performs Cholesky factorization on a symmetric or Hermitian positive definite matrix.
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Performs Cholesky factorization on the rank-1 updated Cholesky matrix. The node performs Cholesky factorization directly on the known factored matrix instead of the updated matrix.
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Generates a real matrix from a specified set of eigenvalues.
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Generates a matrix of a specific type.
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Computes the determinant of a matrix.
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Computes the dot product of two vectors.
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Finds the eigenvalues and right eigenvectors of a square matrix.
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Computes the generalized right eigenvalues and eigenvectors of a pair of square matrices.
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Computes the generalized singular value decomposition (GSVD) of a matrix pair.
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Performs the Hessenberg decomposition of a matrix.
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Finds the inverse of an input matrix, if the inverse exists.
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Calculates the Kronecker product of two input matrices.
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Performs the LU factorization of a matrix.
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Solves the Lyapunov matrix equation.
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Balances a general matrix to improve the accuracy of computed eigenvalues and eigenvectors.
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Computes the characteristic polynomial of a matrix.
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Computes the condition number of a matrix.
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Computes the exponential of a square matrix by using the Pade Approximation method.
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Computes the natural logarithm of a square matrix.
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Computes the norm of a matrix.
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Computes the nth power of a matrix.
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Computes the rank of a matrix.
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Computes the square root of a matrix.
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Computes the outer product of two vectors.
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Finds the pseudoinverse matrix of an input matrix by using singular value decomposition.
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Performs the QR decomposition of a matrix with the option of column pivoting.
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Performs the QZ decomposition of a pair of square matrices.
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Performs the Schur decomposition of a square matrix.
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Solves a linear system Ax = y.
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Computes the angle between column spaces of two matrices.
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Computes the singular value decomposition (SVD) of an m x n matrix.
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Solves the Sylvester matrix equation.
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Determines whether a matrix is of a specific type.
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Finds the trace of a matrix.
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Transposes a matrix.
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Computes the norm of a vector.

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