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4 results for “EEG signal processing”
Figure 5. Process flow of PSO-Classification of Human Emotion from Deap EEG Signal Using Hybrid Improved Neural Networks with Cuckoo Search
<p>PSO is used to identify the best solution from collection of solution. It is a computational<br> method that optimizes a problem by iteratively trying to improve a candidate solution with regard to<br> a given measure of quality. PSO optimizes a problem by having a population of candidate solutions,<br> here dubbed particles, and moving these particles around in the search-space according to simple<br> mathematical formulae over the particle's position and velocity. Each particle's movement is<br> influenced by its local best known position but, is also guided toward the best known positions in<br> the search-space, which are updated as better positions are found by other particles. This is expected<br> to move the swarm toward the best solutions. PSO is a metaheuristic as it makes few or no<br> assumptions about the problem being optimized and can search very large spaces of candidate<br> solutions. However, metaheuristic such as PSO do not guarantee an optimal solution is ever found.<br> The following Figure 5 explains the basic flow of PSO process.</p>
EEG Dataset and Processing script Associated with the Manuscript, "Using the Time-varying Drift Rate, the Signal Suppression and the Utility Maximisation to Account for Road Crossing Decisions".
<p>The repository archived the behavioural data (zip files) associated with the EEG experiment and the MATLAB script for EEG processing. BDFs stored the down-sampled EEG. </p>
Dataset used in the paper "EEG SIGNAL PROCESSING IN MI-BCI APPLICATIONS WITH IMPROVED COVARIANCE MATRIX ESTIMATORS"
<pre>This material is associated with the PhD Thesis of Javier Olias (which is supervised by Sergio Cruces & Ruben Martin) and the paper: <br>J. Olias, R. Martín-Clemente, M. A. Sarmiento-Vega and S. Cruces, "EEG Signal Processing in MI-BCI Applications With Improved Covariance Matrix Estimators," in <em>IEEE Transactions on Neural Systems and Rehabilitation Engineering</em>, vol. 27, no. 5, pp. 895-904, May 2019, doi: 10.1109/TNSRE.2019.2905894.<br> </pre> <div> <div> <div> <div> <p>The paper can be downloaded in open-access format from the following websites:</p> <p>https://hdl.handle.net/11441/154861</p> </div> </div> </div> </div> <div> <div> <div>https://ieeexplore.ieee.org/document/8688582</div> </div> </div>
Electroencephalography (EEG) Signal Processing
ClinicalTrials.gov study NCT01369290. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.