Search Results - (( developing eeg data algorithm ) OR ( java implementation learning algorithm ))
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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2
Hardware Simulator for Seizure, Preseizure and Normal Mode Signal Generation in LabVIEW Environment for Research
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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3
Classification of labour pain using electroencephalogram signal based on wavelet method / 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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Extraction of Inherent Frequency Components of Multiway EEG Data Using Two-Stage Neural Canonical Correlation Analysis
Published 2014“…This paper presents an algorithm for extracting underlying frequency components of massive Electroencephalogram (EEG) data. …”
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
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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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
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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Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization
Published 2018“…Generally, every step of the data processing sequence affects the accuracy of EEG source localization. …”
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Fused multivariate empirical mode decomposition (MEMD) and inverse solution method for EEG source localization
Published 2018“…Generally, every step of the data processing sequence affects the accuracy of EEG source localization. …”
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Bayesian Framework based Brain Source Localization Using High SNR EEG Data
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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“Analysis of EEG Recordings During Grasp and Lift (GAL) Trials
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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EEG-based fatigue detection using binary pattern analysis and KNN algorithm
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Proceeding Paper -
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Fuzzification of epileptic data: an application for prediction and identification of partial seizure
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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14
Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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Bio-signal identification using simple growing RBF-network (OLACA)
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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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Improving EEG Signal Peak Detection Using Feature Weight Learning of a Neural Network with Random Weights for Eye Event-Related Applications
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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Epileptic seizure detection using the singular values of EEG signals
Published 2013“…EEG recordings of 4-paediatric patients with 20 seizures are used to validate the proposed algorithm and the preliminary results indicates good level of sensitivity by the singular values to the changes in the EEG signals due to epileptic seizure. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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