Learning Optimization Using Genetic Algorithm in Post-Stroke EEG Signal Classification

2020 Fifth International Conference on Informatics and Computing (ICIC) ◽

10.1109/icic50835.2020.9288559 ◽

2020 ◽

Author(s):

Esmeralda Contessa Djamal ◽

Mita Amara ◽

Daswara Djajasasmita ◽

Sandy Lesmana Liem Limanjaya

Keyword(s):

Genetic Algorithm ◽

Signal Classification ◽

Eeg Signal ◽

Post Stroke ◽

Eeg Signal Classification

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Learning Optimization Using Genetic Algorithm in Post-Stroke EEG Signal Classification

2020 Fifth International Conference on Informatics and Computing (ICIC) ◽

10.1109/icic50835.2020.9288531 ◽

2020 ◽

Author(s):

Esmeralda Contessa Djamal ◽

Mita Amara ◽

Daswara Djajasasmita ◽

Sandy Lesmana Liem Limanjaya

Keyword(s):

Genetic Algorithm ◽

Signal Classification ◽

Eeg Signal ◽

Post Stroke ◽

Eeg Signal Classification

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EEG Signal Classification Using the Event-Related Coherence and Genetic Algorithm

Advances in Brain Inspired Cognitive Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-38786-9_11 ◽

2013 ◽

pp. 92-100 ◽

Cited By ~ 1

Author(s):

Chunying Fang ◽

Haifeng Li ◽

Lin Ma

Keyword(s):

Genetic Algorithm ◽

Signal Classification ◽

Eeg Signal ◽

Eeg Signal Classification ◽

Event Related Coherence

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EEG signal classification method based on improved empirical mode decomposition and SVM

Journal of Physics Conference Series ◽

10.1088/1742-6596/1846/1/012054 ◽

2021 ◽

Vol 1846 (1) ◽

pp. 012054

Author(s):

Zihao Zhang ◽

Zhiyi Li ◽

Ting Ma ◽

Jiayu Zhao

Keyword(s):

Empirical Mode Decomposition ◽

Signal Classification ◽

Classification Method ◽

Eeg Signal ◽

Mode Decomposition ◽

Eeg Signal Classification

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A motor imagery EEG signal classification algorithm based on recurrence plot convolution neural network

Pattern Recognition Letters ◽

10.1016/j.patrec.2021.03.023 ◽

2021 ◽

Author(s):

XianJia Meng ◽

Shi Qiu ◽

Shaohua Wan ◽

Keyang Cheng ◽

Lei Cui

Keyword(s):

Neural Network ◽

Motor Imagery ◽

Recurrence Plot ◽

Classification Algorithm ◽

Convolution Neural Network ◽

Signal Classification ◽

Eeg Signal ◽

Eeg Signal Classification

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Systems Design for EEG Signal Classification of Sensorimotor Activity Using Machine Learning

2021 IEEE International Systems Conference (SysCon) ◽

10.1109/syscon48628.2021.9447106 ◽

2021 ◽

Author(s):

Jacqueline Heaton ◽

Sidney Givigi

Keyword(s):

Machine Learning ◽

Systems Design ◽

Signal Classification ◽

Eeg Signal ◽

Sensorimotor Activity ◽

Eeg Signal Classification

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A Deep Convolutional Neural Network Framework for EEG Signal Classification

SSRN Electronic Journal ◽

10.2139/ssrn.3970602 ◽

2021 ◽

Author(s):

Aswini A ◽

Sreeraj S

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Deep Convolutional Neural Network ◽

Signal Classification ◽

Eeg Signal ◽

Eeg Signal Classification

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A Comprehensive Analysis on EEG Signal Classification on Human Brain

10.1109/icrito51393.2021.9596296 ◽

2021 ◽

Author(s):

Puranam Revanth Kumar ◽

Sangeetha K ◽

Rabi Narayan Satpathy ◽

Sachi Nandan Mohanty

Keyword(s):

Human Brain ◽

Comprehensive Analysis ◽

Signal Classification ◽

Eeg Signal ◽

Eeg Signal Classification

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EEG Signal Classification for Mental Stress During Arithmetic Task Using Wavelet Transformation and Statistical Features

10.1109/acmi53878.2021.9528230 ◽

2021 ◽

Author(s):

Ariful Islam ◽

Ajay Krishno Sarkar ◽

Tonmoy Ghosh

Keyword(s):

Mental Stress ◽

Wavelet Transformation ◽

Signal Classification ◽

Eeg Signal ◽

Statistical Features ◽

Arithmetic Task ◽

Eeg Signal Classification

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An Analysis of Integration of Hill Climbing in Crossover and Mutation operation for EEG Signal Classification

Proceedings of the 2015 on Genetic and Evolutionary Computation Conference - GECCO '15 ◽

10.1145/2739480.2754710 ◽

2015 ◽

Cited By ~ 1

Author(s):

Arpit Bhardwaj ◽

Aruna Tiwari ◽

M. Vishaal Varma ◽

M. Ramesh Krishna

Keyword(s):

Hill Climbing ◽

Signal Classification ◽

Eeg Signal ◽

Mutation Operation ◽

Eeg Signal Classification ◽

Crossover And Mutation

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An Improved EEG Signal Classification Using Neural Network with the Consequence of ICA and STFT

Journal of Electrical Engineering and Technology ◽

10.5370/jeet.2014.9.3.1060 ◽

2014 ◽

Vol 9 (3) ◽

pp. 1060-1071 ◽

Cited By ~ 17

Author(s):

K. Sivasankari ◽

K. Thanushkodi

Keyword(s):

Neural Network ◽

Signal Classification ◽

Eeg Signal ◽

Eeg Signal Classification

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