Matrix ActiveX Component 3.1

Eigenvalues and Eigenvectors calculation in just one line of your source code

Matrix ActiveX Component is a useful tool that can simplify the use of matrix operations for mathematical computations in application development.

It provides for matrix operations such as addition, subtraction, multiplication, inversion, transpose, and computation of determinant, LU and Cholesky decompositions. Advanced edition additionally supports QR and Singular Value (SVD) decompositions, Eigenvalue and Eigenvector computation for symmetric and non symmetric matrices.

Advanced II edition now supports operations with complex matrices.

The Matrix ActiveX Component delivers all the speed, numerical stability, robustness and scalability you could ask for, significantly reducing development time and allowing you to focus on the actual goals of your application. Without compromising speed, it uses an object-oriented approach to matrix math computation, it provides you with the Matrix and CMatrix Classes containing all the Properties, Methods that you'll need when deploying your numerical exploration.

You may be developing a statistical package, or you might want fast 3D graphics transformations, or you may need to solve simultaneous equations, multivariate linear regressions, or to solve EigenValues and EigenVectors problems, Matrix ActiveX Component can do all of this and more.


Main features of Matrix ActiveX Component:

Eigen Problems

Matrix Decompositions

Basic Matrix Operations

Common Matrix Operations

Simultaneous Equation Solving


Limitations of Matrix ActiveX Component:

limits the maximum matrix size to 6x6

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