Search Results - (( java implementation path algorithm ) OR ( using eeg based algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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3
Eeg-Based Person Identification Using Multi-Levelwavelet Decomposition With Multi-Objective Flower Pollination Algorithm
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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4
Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Finally, the k-nearest neighbors ( kNN) classification technique was used for automatic gender identification of an emotional-based EEG dataset. …”
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Single-trial visual evoked potential extraction using partial least-squares-based approach
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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Single-trial visual evoked potential extraction using partial least-squares-based approach
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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Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks
Published 2014“…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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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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10
Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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11
Dingle's Model-based EEG Peak Detection using a Rule-based Classifier
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Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…Such automated systems must rely on robust and effective algorithms for detection and prediction. Approach: The proposed detection system of epileptic seizure in EEG signals is based on Discrete Wavelet Transform (DWT) and Swarm Negative Selection (SNS) algorithm. …”
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14
Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device
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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15
EEG-and MRI-based epilepsy source localization using multivariate empirical mode decomposition and inverse solution method
Published 2018“…Although Electroencephalography (EEG)-based source localization (ESL) estimates the EZ more precisely than other techniques but, it is used rarely in surgery centers. …”
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16
Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
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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Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion
Published 2017“…Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. …”
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Multivariate EEG signal processing techniques for the aid of severely disabled people
Published 2022“…One reason could be that the researchers in this field (motor imagery based BCI) normally use two to three channels of EEG signal. …”
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Emotion Detection Based on EEG Signal
Published 2021“…Lately, emotion detection through EEG signals had pulled in numerous researchers and numerous algorithm were discovered. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…However, the developed algorithms only consider the selected features from a peak model based on the understanding of the EEG signals characteristics. …”
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