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| Linear Algebra Decomposition | Script |
Triangular Decomposition (LU) |
triangular_decomp.m
|
Cholesky Decomposition (LLT ) |
Cholesky.m |
Spectral Decomposition (LDLT) |
spectral_decomp.m |
| Lanczos Tridiagonalization | Lanczos_tridiagonal.m |
|
Householder
Tridiagonalization, The alternate method uses a more efficient method for the tridiagonalization. The mo version is optimized for Matlab via sparse matrices. The Hessenberg version uses Matlab's hess function. |
supporting functions |
| QR Householder Decomposition | QR_Householder.m |
|
Eigenvalues via the QR Householder algorithm. Two versions. The mo version is optimized for Matlab via sparse matrices. |
|
| Generalized eigenvalue problem | |
| Single Value Decomposition of a matrix. Matlab already has a built-in function to do this, but this script demonstrates the steps | SVD.m |
| Linear Algebra, Matrix Inverse |
|
pseudo inverse of a
matrix using two methods:
|
pseudo_inverse.m |
| QR Householder Method | QR_Householder_inv.m |
| Linear Algebra and Eigenvalues | Matlab Scripts |
| This script find the lowest eigenvalue for the generalized eigenvalue problem | inverse_power_iteration.m |
| This script finds the largest eigenvalue for the generalized eigenvalue problem | power_iteration.m |
| Eigenvalues via the QR Householder algorithm | QR_Householder_eigen.m |
| This program converts the generalized eigenvalue problem to a standarized form | convert_eig.m |
| Modified Gram-Schmidt Orthogonalization | modified_Gram_Schmidt.m |
| Simultaneous iteration example for the generalized eigenvalue problem. |
simultaneous_iteration.m Supporting function: sort_eigenvalues_eigenvectors.m |
| Subspace Iteration |
subspace_iteration.m Supporting function: sort_eigenvalues_eigenvectors.m |
| Sturm Sequence for the Generalized Eigenvalue Problem |
sturm_sequence.m LDLT.m |
| Sturm Sequence for the Generalized Eigenvalue Problem. This is an alternate version which converts the generalized eigenvalue problem to a standard, tridiagonal form. It is faster for large problems. | sturm_sequence_alt.m Supporting Functions: convert_general_standard.m function_Householder_tridiagonal_alt.m M_K_symmetric.m eig_power.m eig_inverse_power.m diagonal_pivot.m Sturm_D.m |
| Mass Condensation (Guyan Reduction) | |
| Single Value Decomposition of a matrix. Matlab already has a built-in function to do this, but this script demonstrates the procedure | SVD.m |
| Single Value Decomposition of a semi-definite, symmetric matrix | SVD_semidefinite_sym.m |
|
pseudo inverse of a matrix using
two methods: 1. SVD 2. Ben-Israel & Cohen iteration |
pseudo_inverse.m |
| Transfer
Functions from Modes: Transfer Functions Page |
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