Search Results for "java matlab"
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Showing 9 open source projects for "java matlab"
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VeriSiMPL
Verification via biSimulations of Max-Plus-Linear models
... are to be expressed in the C++ language. The abstraction procedure runs in C++. The generated LTS is exported to the NuSMV language. As such, it can be fed, along with a specification of interest, to the NuSMV model checker. If you are more familiar with JAVA language, we suggest you to try VeriSiMPL version 2.0 which is fully based on JAVA. If you are more familiar with MATLAB language, we suggest you to try VeriSiMPL version 1.4 which is fully based on MATLAB. -
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Octclipse
Octave Eclipse GUI
Octave development environment built upon Eclipse's Dynamic Languages Toolkit (http://www.eclipse.org/dltk/). Distributed as an Update site for Eclipse 3.7 Indigo and Indigo-based package for several platforms. Supports search, autocompletion, launching scripts, interactive console, debug and integrated plotting on Octave versions 3.2.x, 3.4.x and 3.6.x. The current goal is to make it running out-of-box on multiple platforms. Currently only Linux and Windows are supported. Mac... -
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gfit creates an interface between computational models and experimental data and provides tools for their analysis
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A Matlab toolbox for interfacing with the pure JAVA numerical library Snifflib. This toolbox provides convenience m-files for interoperability with Snifflib from within an active Matlab session running a JAVA virtual machine.
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MATLAB Engine for Java is a library that uses the C API of the MATLAB Engine to: put variables from Java to Matlab, evaluate Matlab commands, get results from Matlab to Java.
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A library of data objects that simulate mathematical neurons, including classic Hodgkin-Huxley neurons and theta neurons.
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VectTens
A library for handling vectors, tensors, and more.
VectTens is an object-oriented numerical library designed to manipulate vectors, tensors, and other mathematical quantities in a simple and efficient manner. -
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This project collect several data mining methods, such as: 1) clustering methods; 2) biclustering methods; 3) FCA methods and etc.
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Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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