Optimizing deep CNN architecture via hybrid Harris Hawks arithmetic algorithm for EEG meditation classification

Key Points

• Improved accuracy in EEG meditation classification is achieved through optimization techniques.
• The hybrid Harris Hawks arithmetic algorithm significantly enhances the deep CNN architecture.
• Assessment utilizes EEG data for classifying meditation states effectively across varied sessions.
• Findings suggest that optimizing neural networks may lead to advancements in brain-computer interface technologies.