Improved Black Widow Optimization Assisted Channel Selection for Motor Imagery BCI:A Non-Parametric Analysis-Reference-Cited by-同舟云学术

Improved Black Widow Optimization Assisted Channel Selection for Motor Imagery BCI:A Non-Parametric Analysis

Published:2022-12-23 Issue: Volume: Page:
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Container-title:2022 International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON)
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Author:

Mandal Sumanta Kumar¹,Bj Naskar M Nazma²

Affiliation:

1. School Of Computer Engineering Kalinga Institute Of Industrial Technology (Kiit) Deemed To Be University,Bhubaneswar,Odisha,India

2. School Of Computer Engineering Kalinga Institute Of Industrial Technology (Kiit), Deemed To Be University,Bhubaneswar,Odisha,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10083316/10083513/10084322.pdf?arnumber=10084322

Reference32 articles.

1. An Automatic Subject Specific Intrinsic Mode Function Selection for Enhancing Two-Class EEG-Based Motor Imagery-Brain Computer Interface

2. Identifying motor imagery activities in brain computer interfaces based on the intelligent selection of most informative timeframe

3. A flexible analytic wavelet transform based approach for motor-imagery tasks classification in BCI applications;taransiuly siuly;Computer Methods and Programs in Biomedicine,2020

4. Fused Group Lasso: A New EEG Classification Model With Spatial Smooth Constraint for Motor Imagery-Based Brain–Computer Interface

5. Black Widow Optimization Algorithm: Optimal Designing and modelling and of LLC Resonant Converter

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