Matrix ActiveX Component 3.1

Matrix ActiveX Component 3.1 is created to 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 youll 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.

It can be used from within any programming language that supports COM objects, such as Visual Basic, .NET Basic, Vbscript, ASP, JavaScript, C++, C#, Delphi and Excel's VBA.

Use it in your source code and see how the Matrix ActiveX Component simplifies your coding tasks.

Whether you are developing a statistical package, seeking fast 3D graphics transformations, looking to solve simultaneous equations, multivariate linear regressions, eigenvalue and eigenvector calculation problems, the Matrix ActiveX Component can do all of this and more!

Finally, you can discover for yourself just how useful and versatile the Matrix ActiveX Component is in all types of matrix math calculations, as well as in its ability to calculate eigenvalues and eigenvectors.

If you program in C#, VB.NET, or managed C++ then the Bluebit .NET Matrix Library is the right tool for you. It provides classes for object-oriented linear algebra in the .NET platform.

It can be used to solve systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalues and eigenvectors problems, and singular value problems. Also provided are the associated matrix factorizations such as Eigen, LQ, LU, Cholesky, QR, SVD.

The above functionality is present for both real and complex matrices. Two analogous sets of classes are provided for real and complex matrices, vectors and factorizations.

While exposing an easy to use and powerful interface,  the Bluebit .NET Matrix Library does not sacrifice any performance. Highly optimized BLAS and the standard LAPACK routines are used within the library and provide fast execution and accurate calculations.

Major Features:

1. Eigen Problems
   • Eigenvalues Eigenvectors of symmetric and non- symmetric matrices *
2. Matrix Decompositions
   • LU Decomposition
   • Cholesky Decomposition
   • QR Decomposition *
   • Singular Value Decomposition (SVD) *
3. Basic Matrix Operations
   • Addition
   • Subtraction
   • Scalar Multiplication
   • Normalize
   • Transpose
4. Common Matrix Operations
   • Multiplication
   • Inversion
   • Determinant
5. Simultaneous Equation Solving
   • Using Matrix Inversion
   • Using Gauss Elimination