PyEEG: an open source Python module for EEG/MEG feature extraction. - Wikidata - awgldk - TriplyDB

PyEEG: an open source Python module for EEG/MEG feature extraction.

PyEEG: an open source Python module for EEG/MEG feature extraction.

http://www.wikidata.org/entity/Q33879551

about

EEGVIS: A MATLAB Toolbox for Browsing, Exploring, and Viewing Large Datasets.A Framework for Content-based Retrieval of EEG with Applications to Neuroscience and Beyond.A Phase-Locked Loop Epilepsy Network Emulator.

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P2860

PyEEG: an open source Python module for EEG/MEG feature extraction.

http://www.wikidata.org/entity/Q33879551

description

2011 nî lūn-bûn

@nan

2011 թուականի Մարտին հրատարակուած գիտական յօդուած

@hyw

2011 թվականի մարտին հրատարակված գիտական հոդված

@hy

2011年の論文

@ja

2011年論文

@yue

2011年論文

@zh-hant

2011年論文

@zh-hk

2011年論文

@zh-mo

2011年論文

@zh-tw

2011年论文

@wuu

name

PyEEG: an open source Python module for EEG/MEG feature extraction.

@ast

PyEEG: an open source Python module for EEG/MEG feature extraction.

@en

type

label

PyEEG: an open source Python module for EEG/MEG feature extraction.

@ast

PyEEG: an open source Python module for EEG/MEG feature extraction.

@en

prefLabel

PyEEG: an open source Python module for EEG/MEG feature extraction.

@ast

PyEEG: an open source Python module for EEG/MEG feature extraction.

@en

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Computational Intelligence and Neuroscience

P1476

PyEEG: an open source Python module for EEG/MEG feature extraction.

@en

P2093

Christina Zhang

http://www.w3.org/2001/XMLSchema#string

Forrest Sheng Bao

http://www.w3.org/2001/XMLSchema#string

Xin Liu

http://www.w3.org/2001/XMLSchema#string

P2860

A regularity statistic for medical data analysis.

Automatic spike detection via an artificial neural network using raw EEG data: effects of data preparation and implications in the limitations of online recognition.

Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series.

Seizure prediction by nonlinear EEG analysis.

Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state.

Quantification of EEG irregularity by use of the entropy of the power spectrum.

Temporal and spatial complexity measures for electroencephalogram based brain-computer interfacing.

Extracting multisource brain activity from a single electromagnetic channel.

A paradigm for epileptic seizure prediction using a coupled oscillator model of the brain.

Localization of seizure onset area from intracranial non-seizure EEG by exploiting locally enhanced synchrony.

P304

406391

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scholarly article

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10.1155/2011/406391

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2011

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2011-03-29T00:00:00Z

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51069705

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21512582

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open-source software

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3070217

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