electroCUDA

Version 0.0.200 (189 Mo) par Kevin Tan
Robust pelectrophysiology tools with GPU acceleration
170 téléchargements
Mise à jour 16 avr. 2024

electroCUDA – see wiki for documentation & theoretical overview

Summary statistics of a highly-localized neuronal source decomposed by electroCUDA
Summary statistics of an independent neuronal source decomposed by electroCUDA

View electroCUDA on File Exchange

ElectroCUDA – robust preprocessing & analysis for electrophysiology. Core features include noise-resistant signal processing, robust statistics & extensive hardware acceleration.

ElectroCUDA is intended for any multichannel field potential recordings (LFP/EEG/MEG), but development has focused on intracranial EEG (ECoG/sEEG) thus far.

Code is Matlab-based with calls to compiled CUDA, C/C++ & Fortran binaries. User-friendly wrappers abstract away all non-Matlab operations. Modular code & data structures facilitate easy interoperability with other packages. Compute performance is maximized via layered hardware acceleration & comprehensive code optimizations.

Development status: PRE-ALPHA

⚠️   Code is not yet validated or peer-reviewed for general use

Acknowledgements

This work was supported by National Science Foundation Graduate Research Fellowship DGE-1650604 and Department of Defense Grant 13RSA281. See wiki for full acknowledgments.

License

ElectroCUDA is free and open-source under GNU GPL 3.0

Terms of use

Use this code at your own risk. Users assume full responsibility for any eventuality related to this code. This code is for research purposes only and is not intended for clinical or medical use.

USE AND DISTRIBUTION OF THIS SOFTWARE MAY BE SUBJECT TO UNIVERSITY OF CALIFORNIA INTELLECTUAL PROPERTY RIGHTS AND UNITED STATES MANDATES FOR FEDERALLY-FUNDED RESEARCH.

THE CONTENT HEREIN IS PROVIDED "AS IS" WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES. IN NO EVENT SHALL THE AUTHORS AND CONTRIBUTORS OF CONTENT HEREIN BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY OR CONSEQUENTIAL DAMAGES AND/OR ADVERSE OUTCOMES RELATED IN ANY WAY TO THE USE OF THIS CONTENT. ANY USE OF THIS CONTENT IMPLIES ACCEPTANCE OF THESE TERMS.

Citation pour cette source

Kevin Tan (2024). electroCUDA (https://github.com/kevmtan/electroCUDA), GitHub. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2022b
Compatible avec les versions R2020a et ultérieures
Plateformes compatibles
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lib

lib/ASR

lib/ASR/private

lib/NoiseTools

lib/NoiseTools/DISUSE

lib/NoiseTools/TEST

lib/NoiseTools/TEST/JUNK

lib/NoiseTools/private

lib/amica-master

lib/cdcol

lib/cleanline-master

lib/cleanline-master/external/bcilab_partial

lib/cleanline-master/external/bcilab_partial/arguments

lib/cleanline-master/external/bcilab_partial/dependencies/CStrAinBP-2009-09-13

lib/cleanline-master/external/bcilab_partial/dependencies/CStrAinBP-2009-09-13/build-Gracing.local

lib/cleanline-master/external/bcilab_partial/dependencies/CStrAinBP-2009-09-13/build-Jordan

lib/cleanline-master/external/bcilab_partial/dependencies/CStrAinBP-2009-09-13/build-bluffing

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lib/cleanline-master/external/shadowplot

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lib/iELVis-master/iELVis_MAIN/iELVis_MATLAB/ELEC_LOC/YANG_WANG2011

lib/iELVis-master/iELVis_MAIN/iELVis_MATLAB/PLOTTING

lib/iELVis-master/iELVis_MATLAB_ADMIN

lib/libsvm-master/matlab

lib/manopt

lib/manopt/checkinstall

lib/manopt/examples

lib/manopt/manopt/autodiff

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lib/manopt/manopt/autodiff/functions_AD

lib/manopt/manopt/core

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lib/manopt/manopt/manifolds/ttfixedrank/TTeMPS_1.1/algorithms/linearsystem

lib/manopt/manopt/manifolds/ttfixedrank/TTeMPS_1.1/examples

lib/manopt/manopt/manifolds/ttfixedrank/TTeMPS_1.1/operators

lib/manopt/manopt/solvers/arc

lib/manopt/manopt/solvers/barzilaiborwein

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lib/manopt/manopt/solvers/gradientapproximations

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lib/manopt/manopt/solvers/linesearch

lib/manopt/manopt/solvers/neldermead

lib/manopt/manopt/solvers/preconditioners

lib/manopt/manopt/solvers/pso

lib/manopt/manopt/solvers/steepestdescent

lib/manopt/manopt/solvers/stochasticgradient

lib/manopt/manopt/solvers/trustregions

lib/manopt/manopt/tools

lib/marguiles

lib/robCov

lib/robCov/private

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lib/wavelet-glaciology

lib/wavelet-glaciology/docs

lib/wavelet-glaciology/faq

lib/wavelet-glaciology/private

lib/zapline-plus-main

src/admin

src/anatomy

src/behav

src/plot

src/plot/cbrewer2

src/plot/cbrewer2/28790/colorspace

src/plot/colormaps

src/plot/distinguishable_colors

src/signal

src/signal/private

src/stats

src/stats/ec_robCov

src/stats/ec_robCov/private

src/stats/ec_robCov/private/test

src/stats/imageSimilarity

src/stats/imageSimilarity/private

src/stats/imageSimilarity/private/ShapeMatcher5.2.1_windows

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src/stats/imageSimilarity/private/wavelets

src/z_depreciated

src/z_testing

user

user/pipeline_KT

user/pipeline_example

Les versions qui utilisent la branche GitHub par défaut ne peuvent pas être téléchargées

Version Publié le Notes de version
0.0.200

see github

0.0.102

Many new CUDA implementations: continuous wavelet transform (single & double), CWT scale spectrum (single & double), robust detrending, zero-phase filtering, VLFeat convolutional neural nets & computer vision models, AMICA on GPU (semi-functional)

0.0.101

GPU optimizations for CWT & ec_abs2norm... added validation functions 'isany' & 'istext'

0.0.1

Pour consulter ou signaler des problèmes liés à ce module complémentaire GitHub, accédez au dépôt GitHub.
Pour consulter ou signaler des problèmes liés à ce module complémentaire GitHub, accédez au dépôt GitHub.