Showing 5 open source projects for "information technology"

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    Armadillo

    Armadillo

    fast C++ library for linear algebra & scientific computing

    * Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:...
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    Downloads: 2,943 This Week
    Last Update:
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  • 2

    GeoPDEs

    A package for Isogeometric Analysis in Octave and Matlab

    GeoPDEs is a suite of software tools for research on Isogeometric Analysis of PDEs. GeoPDEs is free software implemented in Octave and fully compatible with Matlab. GeoPDEs is no longer developed at SF, and has moved to GitHub. Please visit http://rafavzqz.github.io/geopdes/ The mailing list will remain active. Releases up to 2.0.4 can be found here. From version 2.1.0 onward, see https://github.com/rafavzqz/geopdes
    Downloads: 3 This Week
    Last Update:
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  • 3
    ILNumerics.Net
    math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
    Downloads: 0 This Week
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  • 4
    FrancescoMontorsi ScientificResearch

    FrancescoMontorsi ScientificResearch

    Scientific research work of Francesco Montorsi,Univ. of Modena, Italy

    This project hosts the code and the documents which were created by Francesco Montorsi during his PhD at the University of Modena and Reggio Emilia, Italy, about indoor and outdoor localization and navigation techniques. The code (mostly MATLAB code) is publicly available to enable reproducible research.
    Downloads: 1 This Week
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  • 5
    This project collect several data mining methods, such as: 1) clustering methods; 2) biclustering methods; 3) FCA methods and etc.
    Downloads: 0 This Week
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