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  1. 1
    Classification System for Heart Disease Using Bayesian Classifier

    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…Increase of hearth problem in this world is rising each day. Classification system for heart disease is a system that able to justify whether a patient has heart problem or not. …”
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  2. 2
    Fuzzy modeling using Bat Algorithm optimization for classification

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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    Undergraduates Project Papers
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  3. 3
    Hardware Simulator for Seizure, Preseizure and Normal Mode Signal Generation in LabVIEW Environment for Research

    Hardware Simulator for Seizure, Preseizure and Normal Mode Signal Generation in LabVIEW Environment for Research by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed, Kamel, Nidal

    Published 2013
    “…Here we develop a hardware simulator of the EEG model or to simulator any EEG data set in either .edf or .tdmsot .txtformat from any patient or database depository. …”
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    Non-Citation Index Journal
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  4. 4
    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh

    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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  5. 5
    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition

    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

    Published 2019
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  6. 6
    Extraction of Inherent Frequency Components of Multiway EEG Data Using Two-Stage Neural Canonical Correlation Analysis

    Extraction of Inherent Frequency Components of Multiway EEG Data Using Two-Stage Neural Canonical Correlation Analysis by W Omar Ali Saifuddin, Wan Ismail, A. N. M. Enamul, Kabir

    Published 2014
    “…This paper presents an algorithm for extracting underlying frequency components of massive Electroencephalogram (EEG) data. …”
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  7. 7
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
    “…Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
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  8. 8
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
    “…Hence, this work aims to develop an algorithm using statistical-CSP feature for eye state classification from EEG signal. …”
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  9. 9
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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  10. 10
    Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization

    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
    “…Generally, every step of the data processing sequence affects the accuracy of EEG source localization. …”
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  11. 11
    Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization

    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
    “…Generally, every step of the data processing sequence affects the accuracy of EEG source localization. …”
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  12. 12
    Bayesian Framework based Brain Source Localization Using High SNR EEG Data

    Bayesian Framework based Brain Source Localization Using High SNR EEG Data by Jatoi, M.A., Kamel, N., Gaho, A.A., Dharejo, F.A.

    Published 2019
    “…This research work discusses the results based on synthetically generated EEG data at an SNR level of 12 dB with Gaussian noise added linearly in data matrix. …”
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  13. 13
    “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials

    “Analysis of EEG Recordings During Grasp and Lift (GAL) Trials by Musa, Huwaida

    Published 2018
    “…The purpose of analysing this EEG data is to help develop a prosthetic device that can control an upper limb and generate a power grasp or a pinch grasp involving the thumb and index finger. …”
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    Final Year Project
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  14. 14
    EEG-based fatigue detection using binary pattern analysis and KNN algorithm

    EEG-based fatigue detection using binary pattern analysis and KNN algorithm by Abd Rahman, Faridah, Roslizan, Iszan Uwais Amer, Gunawan, Teddy Surya, Fitriawan, Helmy, Kartiwi, Mira, Habaebi, Mohamed Hadi

    Published 2024
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    Proceeding Paper
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  15. 15
    Fuzzification of epileptic data: an application for prediction and identification of partial seizure

    Fuzzification of epileptic data: an application for prediction and identification of partial seizure by Malik, Aamir Saeed, Nasif, Mohammad Shakir, Kamel , Nidal, Qidwai, U.

    Published 2013
    “…Hence in this proposed system, we introduce fuzzification of epileptic EEG data using fuzzy logic interface to classify partial seizure EEG signals from the normal EEG. …”
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    Citation Index Journal
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  16. 16
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  17. 17
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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  18. 18
    Web-based expert system for material selection of natural fiber- reinforced polymer composites

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…So, the integration of Artificial Neural Network (ANN) with an Expert System for material classification was explored. The computational tool, Matlab was proposed for classification with Levenberg-Marquardt training algorithm, which provided faster rate of convergence for feed forward network. …”
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  19. 19
    Bio-signal identification using simple growing RBF-network (OLACA)

    Bio-signal identification using simple growing RBF-network (OLACA) by Asirvadam , Vijanth Sagayan, McLoone, Sean, Palaniappan, R

    Published 2007
    “…These algorithms are developed primarily for applications with fast sampling rate which demands significant reduction in computation load per iteration. …”
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  20. 20
    Improving EEG Signal Peak Detection Using Feature Weight Learning of a Neural Network with Random Weights for Eye Event-Related Applications

    Improving EEG Signal Peak Detection Using Feature Weight Learning of a Neural Network with Random Weights for Eye Event-Related Applications by Asrul, Adam, Zuwairie, Ibrahim, Norrima, Mokhtar, Mohd Ibrahim, Shapiai, Cumming, Paul, Marizan, Mubin

    Published 2017
    “…The optimization of peak detection algorithms for electroencephalogram (EEG) signal analysis is an ongoing project; previously existing algorithms have been used with different models to detect EEG peaks in various applications. …”
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