Open Source MATLAB Research Software
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MATLAB Research Software
View 83 business solutionsBrowse free open source MATLAB Research Software and projects below. Use the toggles on the left to filter open source MATLAB Research Software by OS, license, language, programming language, and project status.
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GNSS-SDR
An open source software-defined GNSS receiver
An open source software-defined Global Navigation Satellite Systems (GNSS) receiver written in C++ and based on the GNU Radio framework. -
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DeepSqueak
DeepSqueak Using Machine Vision to Accelerate Bioacoustics Research
Using Machine Vision to Accelerate Bioacoustics Research. -
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Artifact GeoMorph Toolbox 3D 3.1
A toolbox for 3DGM shape analysis of archaeological artifacts
The Artifact Geomorph Toolbox 3D software is designed to provide the archaeologist interested in artifact shape variability with a toolbox to allow the acquisition, analysis and results exploration of homologous 3D landmark-based geometric morphometric data. As such, the toolbox contains an automated item and semi-landmarks positioning procedure and the fundamental statistical analyses and procedures to allow the processing and analysis of the data. It is designed to be easy to use and straightforward with a simple graphical user interface. Furthermore, it provides direct, quantitative and objective results to answer common archaeological research questions with regards to artifact shape variability. -
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Overhead Imagery Research Data Set (OIRDS) - an annotated data library & tools to aid in the development of computer vision algorithms
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software educativo de aplicacion de metaheuristicas sobre problemas de grafos, TSP problema del agente viajero, ruta mas corta, arbol de expansion minima, etc.
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This is a Content Based Image Retrieval Interface with only color features implemented. This is part of a thesis work to analyze the different color features and observe the performance on mainly corel5k images.
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The project contains a matlab package for generating poised lattices and coarse-fine interpolation matrices for high-order adaptive mesh refinement. It accompanies the paper by Qinghai Zhang submitted to Comput. Methods Appl. Mech. Engrg.
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DL For Monaural Source Separation
Deep Recurrent Neural Networks for Source Separation
Deep Recurrent Neural Networks for Source Separation. -
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A framework for solving large systems of linear equations (Ax=b) in a distributed network using different iterative methods. The solver is written on Java, can be run on Windows or Linux. The solver is compatible with either MPICH2 or mpj-express.
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Geospace Analysis Package
MatLab toolbox for magnetospheric and ionospheric science.
A MatLab toolbox with many simple and useful functions for analyzing data from Cluster, Champ and the Swarm missions. Other functions for space plasma physics, magnetospheric and ionospheric research are included. The toolbox is designed to be as simple as possible. Each function can be learned and used individually. See the tutorial in the Files section for a quick introduction. -
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This is a MATLAB implementation of inverse compositional Active Appearance Models (AAMs), as described in the "Active Appearance Models Revisited" paper by Iain Matthews and Simon Baker.
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JSONLab
JSONLab: compact, portable, robust JSON/binary-JSON encoder
JSONLab is a free and open-source JSON/UBJSON/MessagePack encoder and decoder written in the native MATLAB language. It can be used to convert a MATLAB data structure (array, struct, cell, struct array, cell array, and objects) into JSON/UBJSON/MessagePack formatted strings and files, or to parse a JSON/UBJSON/MessagePack file into MATLAB data structure. JSONLab supports nearly all versions of MATLAB and GNU Octave (a free MATLAB clone). The development of JSONLab is currently funded by the US National Institute of Health (NIH) as part of the NeuroJSON project (data portal https://neurojson.io) under grant U24-NS124027. The goal of the NeuroJSON project is to develop scalable, searchable, and reusable neuroimaging data formats and data-sharing platforms. All data produced from the NeuroJSON project will be using JSON/Binary JData formats as the underlying serialization standards and the lightweight JData specification as a language-independent data annotation standard. -
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Jointly optimized BF Assisted AEC
Jointly optimized BF Assisted AEC
This project presents a statistical model of a jointly optimized beamformer-assisted acoustic echo canceler (AEC). The constrained joint optimization problem can be formulated so that it becomes equivalent to the linearly-constrained minimum variance problem. The new formulation leads to analytical models that can be used to predict the transient performance of adaptive wideband beamformers. A stochastic model is derived for the transient and steady-state behaviors of the residual echo power. The convergence analysis provides a stability bound for the adaptation step-size. Monte Carlo simulations can be performed to illustrate the accuracy of the model, which can then used to provide design guidelines. Application of the new model confirms previous experimental findings that the same cancellation performance of a single-microphone AEC can be achieved with a shorter AEC when the possibility of spatial filtering is available. -
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K-Level 2.0 [revised]
An application of leveling network adjustment using Matlab
This is an application of leveling network adjustment based on Matlab. The method used in this application is least square adjustment. User can enter the leveling data directly or by reading a text file. -
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PRIMA
PRIMA is a package for solving general nonlinear optimization problems
PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation for Powell's derivative-free optimization methods, i.e., COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. PRIMA means Reference Implementation for Powell's methods with Modernization and Amelioration, P for Powell. PRIMA is a package for solving general nonlinear optimization problems without using derivatives. It provides the reference implementation for Powell's renowned derivative-free optimization methods, i.e., COBYLA, UOBYQA, NEWUOA, BOBYQA, and LINCOA. The "P" in the name stands for Powell, and "RIMA" is an acronym for "Reference Implementation with Modernization and Amelioration". -
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A particle swarm optimization demo written by students in the digital communication msc program (2010) at uni-kiel.
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The major aim of the Psychtoolbox 3 wrapper is to provide a set of basic tools that allow programming novices the use of the Psychophysics Toolbox without limiting the power and flexibility of the Psychophysics Toolbox and MATLAB.
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diauxic growth model ensemble
An ensemble of models showing diauxic growth behavior
An ensemble of mathematical model is presented that all show diauxic growth behaviour of a bacterial culture. Carbon catabolite repression (CCR) is the main mechanism controlling carbohydrate uptake in bacteria, and therefore also controlling whether or not different carbon sources are metabolized in parallel or sequentially. Although described as a paradigm of the regulation of bacterial metabolism, the underlying mechanisms remain controversial. The models in the ensemble can be categorized according to regulatory, stoichiometric, and physiological constraints and differ from each other on only a single aspect. We distinguish four groups of models: (1) flux balance models that only define reaction kinetics for substrate uptake and by-product excretion, (2) kinetic models without and (3) kinetic models with regulation on the metabolic and/or genetic level, and (4) resource allocation models. -
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eugen library
Public MatLab toolbox for space science.
A MatLab toolbox with many simple and useful functions for analyzing data from Cluster, Champ and the future Swarm missions. Other functions for space science, magnetospheric and ionospheric research are included. The toolbox is designed to be as simple as possible. Each function can be learned and used individually. Check the webpage for the list of functions: http://eugen-library.sourceforge.net/ -
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svmradiusmargin
code for convex formulation of radius-margin based SVM
Matlab code for the novel algorithms presented in the paper Convex formulation for radius-margin based Support Vector Machines
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