Credibility-Adjusted Data-Conscious Clustering Method for Robust EEG Signal Analysis

Credibility-Adjusted Data-Conscious Clustering Method for Robust EEG Signal Analysis

Clustering neurodata, including electroencephalography (EEG) signals, is crucial for brain-computer interface (BCI) and neurological analysis. However, traditional methods struggle with noise, overlapping distributions, and high-dimensional data. This study presents the Credibility-Adjusted Data Con...

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Bibliographic Details
Main Authors: Fatemeh Divan, Teh Ying Wah, Kheng Seang Lim, Ali Seyed Shirkhorshidi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Brain-computer interfaces
machine learning
pattern clustering
pattern recognition
signal processing
Online Access:https://ieeexplore.ieee.org/document/11045428/
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