Showing 7 open source projects for "state-thread"

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  • 1

    OpenRTDynamics

    A framework for implementing real-time control systems

    - - - T H I S P R O J E C T M O V E D T O G I T H U B - - - A framework for the implementation of advanced real-time control systems which uses signal/block-based schematics (like Simulink) extended by several features like state machines and online-exchangeable sub-simulations. Besides, this framework properly handles multiple threads, their communication, allows to synchronise control systems to external events (e.g. variable timers or incoming network packages) and provides many other nice features. 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.
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  • 2
    C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
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  • 3
    namespace ewalena is a set of tools for state space calculations in quantum mechanical problems.
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  • 4
    Based on boost. Thread:mutex-condition queue and map,ACE style thread and Glib style thread pool, loop task. Memory:memory pool. COM:COM object invocation. Language:compiler lexical and grammar analysis. Network:epoll reactor.
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  • 5
    SPServer is a C++ server framework library that implements the Half-Sync/Half-Async and Leader/Follower thread pool patterns. It's based on libevent in order to utilize the best I/O loop on any platform. It include an embedded http server and ssl proxy.
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  • 6
    The Pennsylvania State University's ACM Competition source repository. For fair, free and open competition. For the development of educational materials in the realm of competitive software development.
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  • 7
    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...
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