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The Jacobi Method has been generalized to complex Hermitian matrices, general nonsymmetric real and complex matrices as well as block matrices. Since singular values of a real matrix are the square roots of the eigenvalues of the symmetric matrix = it can also be used
The complex unitary rotation matrices R pq can be used for Jacobi iteration of complex Hermitian matrices in order to find a numerical estimation of their eigenvectors and eigenvalues simultaneously. Similar to the Givens rotation matrices , R pq are defined as:
Given an n × n square matrix A of real or complex numbers, an eigenvalue λ and its associated generalized eigenvector v are a pair obeying the relation [1] =,where v is a nonzero n × 1 column vector, I is the n × n identity matrix, k is a positive integer, and both λ and v are allowed to be complex even when A is real.l When k = 1, the vector is called simply an eigenvector, and the pair ...
Davidson methods such as Generalized Davidson and Jacobi-Davidson. Conjugate gradient methods such as LOBPCG. A contour integral solver (CISS). Interface to some external eigensolvers, such as ARPACK and BLOPEX. Customization options include: number of wanted eigenvalues, tolerance, size of the employed subspaces, part of the spectrum of interest.
In numerical linear algebra, the Jacobi method (a.k.a. the Jacobi iteration method) is an iterative algorithm for determining the solutions of a strictly diagonally dominant system of linear equations. Each diagonal element is solved for, and an approximate value is plugged in. The process is then iterated until it converges.
It is generally used in solving non-linear equations like Euler's equations in computational fluid dynamics. Matrix-free conjugate gradient method has been applied in the non-linear elasto-plastic finite element solver. [7] Solving these equations requires the calculation of the Jacobian which is costly in terms of CPU time and storage. To ...
Numerical linear algebra is the intersection of numerical analysis and linear algebra: its purpose is the design and analysis of algorithms for the numerical solution of matrix problems. The most important problems are the solution of a system of linear equations and the determination of eigenvalues .
Free: Linux, Windows: CalculiX: It is an Open Source FEA project. The solver uses a partially compatible ABAQUS file format. The pre/post-processor generates input data for many FEA and CFD applications: Guido Dhondt, Klaus Wittig: 2.20: 2022-08-01: GNU GPL: Free: Linux, Windows: DIANA FEA