1.1 Product Features

The features of NMath Matrix include:

• Full-featured structured sparse matrix classes, including triangular, symmetric, Hermitian, banded, tridiagonal, symmetric banded, and Hermitian banded.
• Support for four datatypes: single- and double-precision floating point numbers, and single- and double-precision complex numbers.
• Functions for converting between general matrices and structured sparse matrix types.
• Functions for transposing structured sparse matrices, computing inner products, and calculating matrix norms.
• Overloaded arithmetic operators with their conventional meanings for those .NET languages that support them, and equivalent named methods (Add(), Subtract(), and so on) for those that do not.
• Classes for factoring structured sparse matrices, including LU factorization for banded and tridiagonal matrices, Bunch-Kaufman factorization for symmetric and Hermitian matrices, and Cholesky decomposition for symmetric and Hermitian positive definite matrices. Once constructed, matrix factorizations can be used to solve linear systems and compute determinants, inverses, and condition numbers.
• Orthogonal decomposition classes for general matrices, including QR decomposition and singular value decomposition (SVD).
• Advanced least squares factorization classes for general matrices, including Cholesky, QR, and SVD.
• Classes for solving symmetric, Hermitian, and nonsymmetric eigenvalue problems.
• Fully persistable data classes using standard .NET mechanisms.

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