MWF-based EEG artifact removal in MATLAB
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Updated
Jun 11, 2024 - MATLAB
MWF-based EEG artifact removal in MATLAB
Data repository for the paper of the same name.
This repository contains scripts from published or submitted manuscripts.
The Simulink Model Mutation Testing project provides a framework for generating mutants, and CSV file as an output. It utilizes the MATLAB environment to load the model, apply mutations, and collect outputs.
Code used for processing proteomics data associated with the publication by Yan et al., submitted to Nature Communications in 2024
Code to accompany Significance article "We're not getting any younger! Or should that be older?".
This project represents the implementation of the Enhanced Spatio-Temporal Image Encoding used in the paper "Enhanced Spatio- Temporal Image Encoding for Online Human Activity Recognition" published in the "International Conference on Machine Learning and Applications (ICMLA) 2023".
This project represents the implementation of the Spatio-Temporal Image Encoding used in the paper "Human Activity Recognition: A Spatio-temporal Image Encoding of 3D Skeleton Data for Online Action Detection" published in the "International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications(VISAPP) 2022".
Code for simulating aperiodic EEG signals and detrending EEG spectra, as well as generating figures used in manuscript.
Publicly available code from my publications
Code to support manuscript 'Predicting severe pain after major surgery: a secondary analysis of the Peri-operative Quality Improvement Programme (PQIP) dataset'
Reproducible code for manuscript "Venn diagram analysis overestimates the extent of circadian rhythm reprogramming" published in FEBS Journal
QuantEase, a layer-wise quantization framework, frames the problem as discrete-structured non-convex optimization. Our work leverages Coordinate Descent techniques, offering high-quality solutions without the need for matrix inversion or decomposition.
R Code corresponding to the paper "Outlier detection in network revenue management".
This repo contains the code for implementing example 3.1 of paper Invariance Principle and the Asymptotic Behavior of T-S Fuzzy Systems.
Ultrasound Brain Tomography: Comparison of Deep Learning and Deterministic Methods
📝 A Gaussian-process-model-based approach for robust, independent, and implementation-agnostic validation of complex multi-variable measurement systems: application to SAR measurement systems
This repository contains the scripts used for the following publication: Kong, P. W., Iskandar, M. N. S., Koh, A. H., Ho, M. Y. M., & Lim, C. X. E. (2023). Validation of In-Shoe Force Sensors During Loaded Walking In Military Personnel. Sensors. 23(14), 6465.
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