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July 1, 2024International Journal of Imaging Systems and Technology

A Hybrid Deep Learning Framework Using Scaling‐Basis Chirplet Transform for Motor Imagery EEG Recognition in Brain–Computer Interface Applications

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Authors

MKManvir KaurRURahul UpadhyayVKVinay Kumar

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Cite This Study

Kaur et al. (2024) studied this question.

synapsesocial.com/papers/68e61df7b6db6435875b013ahttps://doi.org/10.1002/ima.23127
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  1. 1Deep learning-based EEG motor imagery signal classification for brain–computer interface applications2026
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  4. 4Feature Extraction and Classification of Motor Imagery EEG Signals in Motor Imagery for Sustainable Brain–Computer Interfaces2024 · 14 citations
  5. 5Optimization of Low-Channel EEG Configurations and Temporal Segmentation for Motor Imagery Classification Using a Flexible EEGNet Framework2026