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concept | DiagonalizeTraits< FT, dim > |
| Concept providing functions to extract eigenvectors and eigenvalues from covariance matrices represented by an array a , using symmetric diagonalization. For example, a matrix of dimension 3 is defined as follows: \( \begin{bmatrix} a[0] & a[1] & a[2] \\ a[1] & a[3] & a[4] \\ a[2] & a[4] & a[5] \\ \end{bmatrix}\) More...
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concept | NormalEquationSparseLinearAlgebraTraits_d |
| Concept describing the set of requirements for solving the normal equation \( A^t A X = A^t B \), \( A \) being a matrix, \( At \) its transpose matrix, \( B \) and \( X \) being two vectors. More...
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concept | SparseLinearAlgebraTraits_d |
| The concept SparseLinearAlgebraTraits_d is used to solve sparse linear systems A \( \times \) X = B. More...
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concept | SparseLinearAlgebraWithFactorTraits_d |
| Concept describing the set of requirements for a direct sparse linear system solver with factorization. A model of this concept stores the left-hand matrix (denoted \( A \)) and provides an additional factorization method to solve the system for different right-hand vectors. More...
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concept | SvdTraits |
| The concept SvdTraits describes the linear algebra types and algorithms needed to solve in the least square sense a linear system with a singular value decomposition. More...
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