Matrix ActiveX Component Advanced
|License:||Free to try|
|Op. System:||Windows Me|
|Last updated:||15 Jul. 2011|
|File size:||486 KB|
Publisher description for Matrix ActiveX Component Advanced
EigenValues and EigenVectors calculation can now become just one line of source code! The ability to calculate EigenValues and EigenVectors is just one aspect of matrix algebra that is featured in the new Advanced edition of Matrix ActiveX Component. Implementing even a simple matrix math operation in your application requires that a matrix algorithm be developed, source coded and extensively tested. Matrix ActiveX Component does this for you! It 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, Matrix ActiveX Component uses an object-oriented approach to matrix mathematical computation. It provides you with the Matrix Class containing all the Properties, Methods and Events that youll need when deploying your numerical exploration. Here are just a few of the supported operations: Basic matrix operations Addition Subtraction Transpose Scalar Multiplication Normalize Common matrix operations Multiplication Inversion Determinant Simultaneous Equations Solving Using matrix inversion Using Gauss elimination Matrix Decompositions LU Decomposition Cholesky Decomposition QR Decomposition* Singular Value Decomposition (SVD)* Eigen problems EigenValues* EigenVectors* Vector functions Column Vector* Row Vector* Events Notification OnProgress Event* Done Event* (*) Only in Advanced edition High-performance matrix calculation is no longer a privilege of mainframe computers running Fortran libraries. Matrix ActiveX Component brings these functions to your desktop application, no matter what your needs! You may be developing a statistical package, or you might want fast 3D graphics transformations. 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! You might expect a tool so robust and versatile to be complicated to use. On the contrary, you will discover how easy, quick and clean your source code can be when you use the Matrix ActiveX Component. Comprehensive documentation is provided that will make it very easy for you to start coding right away. Context-sensitive help is available while debugging. Plenty of source code examples are given throughout, explaining the use of every feature. In addition, we provide online help, and above all, we are always here at your disposal to help you use Matrix ActiveX Component.