Showing 6 open source projects for "linux-libre kernel"

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  • 1
    Volterra2.0

    Volterra2.0

    Volterra series Identification Tool

    Orthogonal method for the Identification of Volterra series. It is an extension of Lee-Schetzen method with two major improvments: 1. Reduced identification uncertainty in diagonal kernel points. 2. Possibility to identify each Volterra kernel with an input with different variance. This feature reduces the identification noise on lower order kernels and improve the "resolution" on higher order kernels. For reference see: Simone Orcioni. Improving the approximation ability of...
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  • 2
    riboshape

    riboshape

    Predicting ribosome footprint profile shapes from transcript sequences

    Riboshape is a suite of algorithms to predict ribosome footprint profile shapes from transcript sequences. It applies kernel smoothing to codon sequences to build predictive features, and uses these features to builds a sparse regression model to predict the ribosome footprint profile shapes. Reference: Liu, T.-Y. and Song, Y.S. Prediction of ribosome footprint profile shapes from transcript sequences. Proceedings of ISMB 2016, Bioinformatics, Vol. 32 No. 12 (2016) i183-i191.
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  • 3
    Qi - Quantitative Imaging (PIV and more)

    Qi - Quantitative Imaging (PIV and more)

    A collection of MATLAB tools for PIV, PTV, particle sizing, and more.

    Qi is a collection of MATLAB tools for the quantitative analysis of flow field images. Our Particle Image Velocimetry (PIV) tool, prana, implements a Robust Phase Correlation kernel for PIV analysis, and now includes Particle Tracking Velocimetry and sizing tools. Tools for pressure calculation, proper orthogonal decomposition (POD), and 3d imaging are under development.
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  • 4
    An implementation of the Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method for MATLAB and R. The supplied functionality includes e.g. cross-validation, kernel parameter optimization, model diagnostics and plot tools.
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  • 5

    CRUMp

    A probabilistic prediction system of protein phosphorylation sites

    CRUMp is based on a kernel-based learning method called Classification Relevance Units Machine (CRUM). Given an input set of protein sequences in FASTA format, the system outputs the position, residue type (S, T, or Y), and the estimated probability of each tested site being phosphorylatable. Latest downloadable files: - crump-0.2.0.tar.gz: CRUMp GNU Octave package - crump-0.2.0.zip: CRUMp MATLAB script - crumptestset.fasta: A testing dataset in FASTA format. The sequence headers list...
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  • 6
    A library for fast computation of Gauss transforms in multiple dimensions, using the Improved Fast Gauss Transform and Approximate Nearest Neighbor searching. This library is useful for efficient Kernel Density Estimation (KDE) using a Gaussian kernel.
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