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Matrix ActiveX Component

The 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. Matrix ActiveX Component is licensed as shareware, the cost of the registered verison is $49 and full size of the download is 0.46 MB. You may download a free version of Matrix ActiveX Component by following download link at Free Download section of this page. Matrix ActiveX Component is developed or distributed by Bluebit Software and is listed under activex activex components maths matrix library.

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Implement matrices for mathematical computations in your applications.

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Free Download

Download URL:	Download Now!
Publisher:	Bluebit Software
Cost:	$49
License Type:	Demo
File Size:	0.46 MB
Release Date:	3/1/2004
Platform: Win98,WinME,WinNT 4.x,Windows2000,WinXP
Keywords:	lu eigenvector eigenvectors decomposition math qr matrix eigenvalues cholesky svd eigenvalue

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