Search Results - (( developing eeg data algorithm ) OR ( java application optimized algorithm ))
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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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Non-Citation Index Journal -
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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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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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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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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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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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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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Thesis -
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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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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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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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