
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...


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...


concept  SparseLinearAlgebraTraits_d 
 The concept SparseLinearAlgebraTraits_d is used to solve sparse linear systems A \( \times \) X = B. More...


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 lefthand matrix (denoted \( A \)) and provides an additional factorization method to solve the system for different righthand vectors. More...


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...

