Showing 6 open source projects for "can"

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  • 1
    FieldTrip

    FieldTrip

    The MATLAB toolbox for MEG, EEG and iEEG analysis

    ...It supports the data formats of all major MEG systems (CTF, Neuromag/Elekta/Megin, BTi/4D, Yokogawa/Ricoh, FieldLine) and of most popular EEG systems, and new formats can be added easily. FieldTrip contains high-level functions that you can use to construct your own analysis protocols in MATLAB. Furthermore, it easily allows methods researchers to incorporate new methods for EEG/MEG analysis.
    Downloads: 0 This Week
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  • 2
    STK

    STK

    a Small (Matlab/Octave) Toolbox for Kriging

    The STK is a (not so) Small Toolbox for Kriging. Its primary focus in on the interpolation / regression technique known as kriging, which is very closely related to Splines and Radial Basis Functions, and can be interpreted as a non-parametric Bayesian method using a Gaussian Process (GP) prior. The STK also provides tools for the sequential and non-sequential design of experiments. Even though it is, currently, mostly geared towards the Design and Analysis of Computer Experiments (DACE), the STK can be useful for other applications areas (such as Geostatistics, Machine Learning, Non-parametric Regression, etc.).
    Downloads: 10 This Week
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  • 3
    A Matlab software routine to perform Principal Component Analysis using Covariance, Correlation or Comedian as the criterion. Though, initially developed for experiments related to fretting wear but can be effectively used to interpret experimental data from any field. The attached files contain source code as well as a sample MATLAB (.mat) data file of 13 variables. It could be replaced to the data file of your choice. The code is open source but you are requested to give credits if used. Additionally, it also has some useful functions for exporting and generating publication quality figures for different kind of figures in MATLAB
    Downloads: 0 This Week
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  • 4
    Matrix factorization is applied to the B-spline basis to construct an orthonormal basis. Data can be approximated by a linear combination of the orthonormal basis functions. Constraints are imposed such that the fitted function is linear at the boundary points, as in natural cubic spline.
    Downloads: 0 This Week
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  • 5

    abc-sde

    approximate Bayesian computation for stochastic differential equations

    ...Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. Variance components for the "measurement error" affecting the data/observations can be estimated. A 50-pages Reference Manual is provided with two case-studies implemented and discussed. The methodology is based on the research article available at http://arxiv.org/abs/1204.5459 Author's research page is http://www.maths.lth.se/matstat/staff/umberto/
    Downloads: 0 This Week
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  • 6
    ...Nevertheless the toolbox capabilities to simulate numerical solutions of SDE systems are still valid and can serve as a useful starting point to those willing to simulate stochastic dynamical models easily.
    Downloads: 1 This Week
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