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mudecompositiontests

Reporsitory to reproduce the results presented in 'Revisiting convolutive blind source separation for identifying spiking motor neuron activity: From theory to practice'

https://github.com/klotz-t/mudecompositiontests

Science Score: 49.0%

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    CITATION.cff file
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    DOI references
    Found 6 DOI reference(s) in README
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    Links to: zenodo.org
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    Low similarity (8.3%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Reporsitory to reproduce the results presented in 'Revisiting convolutive blind source separation for identifying spiking motor neuron activity: From theory to practice'

Basic Info
  • Host: GitHub
  • Owner: klotz-t
  • License: mit
  • Language: MATLAB
  • Default Branch: main
  • Homepage:
  • Size: 152 MB
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 3
Created almost 2 years ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

Description

This repository contains Matlab codes to replicate the data presented in Klotz and Rohlen (2025) "Revisiting convolutive blind source separation for identifying spiking motor neuron activity: From theory to practice", Journal of Neural Engineering, http://dx.doi.org/10.1088/1741-2552/adf886

Installation

  1. You need a working MATLAB installation

  2. Clone the repository: bash git clone https://github.com/klotz-t/MUDecompositionTests.git

Requirements

  1. Matlab2024a
  2. Signal Processing Toolbox
  3. Statistics and Machine Learning Toolbox
  4. Parallel Computing Toolbox

Repository structure

MUDecompositionTests/ experimental-simulation/ % Contains the scripts used to extract the experimental MUAPs (+ a copy of the MUAPs we have used) Figures/ % Scripts for replicating the simulations and figures presented in the paper (+ replication data) Functions/ % Functions used for the upper bound decompositions + utility functions LIF Model/ % Implementation of the utilized leaky-integrate and fire model and functions for simulating EMG signals README.md

Run an in silico experiment and decompose the data

  1. Open Matlab and browse to the folder hosting a copy of the repository

  2. Browse to the Figures folder by entering the following command into your terminal: bash cd Figures/

  3. Run a script of interest via your Matlab terminal, e.g.,: bash generate_figure4

DOI

DOI

Owner

  • Login: klotz-t
  • Kind: user

GitHub Events

Total
  • Release event: 3
  • Watch event: 1
  • Push event: 77
  • Create event: 3
Last Year
  • Release event: 3
  • Watch event: 1
  • Push event: 77
  • Create event: 3