Showing 6 open source projects for "programming c"

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  • 1
    moebinv

    moebinv

    C++ libraries for manipulations in non-Euclidean geometry

    ...The source is written in literate programming NoWeb.
    Downloads: 7 This Week
    Last Update:
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  • 2

    OpenRTDynamics

    A framework for implementing real-time control systems

    ...Because of a high-level schematic-description language -- in form of provided Scilab commands -- only a minimal implementation-effort (no error-prone C-programming) is required.
    Downloads: 0 This Week
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  • 3
    Bat2015

    Bat2015

    Bachelor of Science (Informatik)

    The toolkit glpk supports methods for mixed integer linear programming (MILP). These methods solve Capital Budgeting Problems (CBP). Unfortunately, glpk does not support any multithreading and there is no feature to distribute problems via network connections. Today, this is a pitiable sight, because modern computer systems are coupled by networks and support multi threading. We create a distributed system with Apache thrift and the C-API of glpk.
    Downloads: 0 This Week
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  • 4

    OpenAxiom: Scientific Computation System

    A system for computer algebra and symbolic mathematics

    OpenAxiom is an open source Computer Algebra System. It offers an interactive environment, an expressive programming language, a compiler, a large set of mathematical libraries of interest to researchers and practitioners of computational sciences.
    Downloads: 0 This Week
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  • 5
    This project aims to build a portable pure C++ framework for GPGPU operations. It is conceived to ease scientific researches that need to speed up algebric and calculus operations on normal hardware, without the need of graphic programming knowledge.
    Downloads: 0 This Week
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  • 6
    DBNL

    DBNL

    Dynamic Bayesian Network Library

    DBNL is a cross-platform library that offers a variety of implementations of Bayesian networks and machine learning algorithms. It is a flexible library that covers all aspects of Bayesian netwoks from representation to reasoning and learning. It allows you to create simple static networks as well as complex temporal models with changing structure. It can handle highly non-linear dependencies between multivariate random variables. The particle based inference can answer arbitrary...
    Downloads: 0 This Week
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