Search Results - (( java application optimized algorithm ) OR ( using eeg problem algorithm ))
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Multivariate EEG signal processing techniques for the aid of severely disabled people
Published 2022“…Many studies have revealed the correlation of mental tasks with the EEG signals for actual or fictional movements. However, the performance of Brain Computer Interface (BCI) using EEG signal is still below enough to assist any disabled people. …”
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Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals
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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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Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device
Published 2021“…One of the proposals that could help solve this problem is the use of brain-computer interface (BCI)s. …”
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Detection of eye movements based on EEG signals and the SAX algorithm
Published 2018“…The patients may use a portable electroencephalography (EEG) device to give instruction to a computing device via eye movements. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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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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EEG-based fatigue detection using binary pattern analysis and KNN algorithm
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Optimization of least squares support vector machine technique using genetic algorithm for electroencephalogram multi-dimensional signals
Published 2016“…Discrete wavelet packet transform (DWPT) has been used to extract EEG signals feature and ultimately 204,800 features from 32 subject-independent have been obtained. …”
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Comparison on performance of adaptive algorithms for eye blinks removal in electroencephalogram
Published 2018“…To overcome this problem, an algorithm to automatically detect and remove the artifacts from EEG signals is highly desirable. …”
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EEG-based brain source localization using visual stimuli
Published 2016“…FDM is used for head modelling to solve forward problem. …”
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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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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification
Published 2019“…Thus, we propose an adaptive multi-parent crossover Genetic Algorithm (GA) for optimizing the features used in classifying epileptic seizures. …”
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Bayesian Framework based Brain Source Localization Using High SNR EEG Data
Published 2019“…The brain signals are recorded through neuroimaging techniques such as MEG, EEG, fMRI and PET etc. Nevertheless, when EEG signals are used to reconstruct the active brain sources, then its termed as EEG source localization. …”
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An Enhanced Wavelet Neural Network Model For Epileptic Seizure Detection And Prediction
Published 2016“…The contribution of this thesis is threefold. Firstly, the HS algorithm is used in the feature selection stage. The HS algorithm, which is originally used for optimization problems involving real numbers, is modi�ed and employed in the task of feature selection, which involves binary values.…”
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Detection of Epileptic EEG Signal Using Wavelet Transform and Adaptive Neuro-Fuzzy Inference System
Published 2011“…Such algorithms use brain electrical activity signals called electro encephalography (EEG) and have 2 methods of detection: visual (by specialist inspection) and automatic (by using signal processing knowledge). …”
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