Search Results - (( java _ implementation algorithm ) OR ( using eeg using algorithm ))

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  1. 1

    Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm by Sulaiman, Suriani, Ahmed Yahya, Saba, Mohd Shukor, Nur Sakinah, Ismail , Amelia Ritahani, Zaahirah, Qazi, Yaacob, Hamwira, Abdul Rahman, Abdul Wahab, Dzulkifli, Mariam Adawiah

    Published 2015
    “…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. …”
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    Proceeding Paper
  2. 2

    Eeg-Based Person Identification Using Multi-Levelwavelet Decomposition With Multi-Objective Flower Pollination Algorithm by Yahya Alyasseri, Zaid Abdi Alkareem

    Published 2020
    “…For addressing these points, a novel person identification method that is using EEG with multi-level wavelet decomposition and multi-objective flower pollination algorithm is proposed in this thesis. …”
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    Thesis
  3. 3
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    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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    Thesis
  5. 5

    Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm by Mehrkanoon, S., Moghavvemi, M., Fariborzi, H.

    Published 2007
    “…The EEG signal is most useful for clinical diagnosis and in biomedical research. …”
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    Conference or Workshop Item
  6. 6

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…Today, with online marketing, banking, healthcare and other services, even the average householder is aware of encryption. The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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    Final Year Project
  7. 7

    Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

    Published 2009
    “…The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
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    Article
  8. 8

    Single-trial visual evoked potential extraction using partial least-squares-based approach by Yanti, D.K., Yusoff, M.Z., Asirvadam, V.S.

    Published 2016
    “…For P100, the proposed PLS algorithm is able to provide comparable results to the generalized eigenvalue decomposition (GEVD) algorithm, which alters (prewhitens) the EEG input signal using the prestimulation EEG signal. …”
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    Article
  9. 9

    Single-trial visual evoked potential extraction using partial least-squares-based approach by Yanti, D.K., Yusoff, M.Z., Asirvadam, V.S.

    Published 2016
    “…For P100, the proposed PLS algorithm is able to provide comparable results to the generalized eigenvalue decomposition (GEVD) algorithm, which alters (prewhitens) the EEG input signal using the prestimulation EEG signal. …”
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    Article
  10. 10
  11. 11

    Epileptic Seizure Detection Using Singular Values And Classical Features Of EEG Signals by Ahmed, Ahmed Elsayed Elmahdy

    Published 2014
    “…The proposed algorithm was tested through using CHB-MIT Scalp EEG Database which was recorded in the children hospital in Boston. …”
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    Final Year Project
  12. 12

    Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization by Khosropanah, Pegah, Ramli, Abdul Rahman, Lim, Kheng Seang, Marhaban, Mohammad Hamiruce, Ahmedov, Anvarjon

    Published 2018
    “…High accuracy results of proposed algorithm using non-invasive and low-resolution EEG provide the potential of using this work for pre-surgical evaluation towards epileptogenic zone localization in clinics.…”
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    Article
  13. 13

    Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization by Khosropanah, Pegah, Ramli, Abdul Rahman, Lim, Kheng Seang, Marhaban, Mohammad Hamiruce, Ahmedov, Anvarjon

    Published 2018
    “…High accuracy results of proposed algorithm using non-invasive and low-resolution EEG provide the potential of using this work for pre-surgical evaluation towards epileptogenic zone localization in clinics.…”
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    Article
  14. 14

    Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation by Moghavvemi, M., Mehrkanoon, S.

    Published 2009
    “…BSS algorithm is used to demix the EEG signal into signals with independent features. …”
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    Article
  15. 15

    Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Md. Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

    Published 2019
    “…The differential evolution-based channel selection algorithm (DEFS_Ch) was computed to find the most suitable EEG channels that have the greatest efficacy for identifying the various emotional states of the brain regions. …”
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    Conference or Workshop Item
  16. 16

    Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device by Shanmuga, Pillai A/L Murutha Muthu

    Published 2021
    “…In order to make BCI useful, one of the approaches is to classify the EEG time series signal that may indicate given eye movements that will be used as input instructions to a device. …”
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    Thesis
  17. 17

    EEG Different Frequency Sound Response Identification using Neural Network and Fuzzy Techniques by Wan Daud, Wan Mohd Bukhari, Sudirman , R, Koh, A. C, Safri, N.M, Mahmood, N.H

    Published 2010
    “…Principle Component algorithm, Discrete Wavelet Transform and Fast Fourier Transform, are applied onto the raw EEG signal to extract useful information and specific characteristics from the EEG signals. …”
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    Article
  18. 18

    EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method by Khosropanah, Pegah

    Published 2018
    “…In the current study, clinical dataset of 20 subjects were used to examine sLORETA andWMN fed by raw EEG signals and MEMD features on each patient’s realistic head model. sLORETA in combination with MEMD feature after eye blink removal proved to be a reliable ESL algorithm with 100% accuracy. …”
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    Thesis
  19. 19

    BRAIN ACTIVITIES FOR MOTOR MOVEMENT by ., WAFAA ELSAYED ELBASTY

    Published 2012
    “…The research covers the procedure of designing the BCI algorithm and this consists of three stages firstly recording EEG brain signals, secondly EEG signals pre-processing, Last stage is EEG signals classification. …”
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    Final Year Project
  20. 20

    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

    Published 2014
    “…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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    Conference or Workshop Item