eeglab package (matlab) Search Results


matlab software package  (MathWorks Inc)
96
MathWorks Inc matlab software package
Matlab Software Package, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/MATLAB+Compiler/pm39733553-86-15-15
Average 96 stars, based on 1 article reviews
matlab software package - by Bioz Stars, 2026-09
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interactive matlab toolbox  (MathWorks Inc)
96
MathWorks Inc interactive matlab toolbox
Interactive Matlab Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/Database+Toolbox/arxiv__1207__5933-86-14-15
Average 96 stars, based on 1 article reviews
interactive matlab toolbox - by Bioz Stars, 2026-09
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rstudio 0.98.501  (RStudio)
90
RStudio rstudio 0.98.501
Rstudio 0.98.501, supplied by RStudio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/rstudio+version+0+98+1091/pmc04986540-109-28-28
Average 90 stars, based on 1 article reviews
rstudio 0.98.501 - by Bioz Stars, 2026-09
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eeglab  (SourceForge net)
90
SourceForge net eeglab
Eeglab, supplied by SourceForge net, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/eeglab/pmc07809483-207-33-37
Average 90 stars, based on 1 article reviews
eeglab - by Bioz Stars, 2026-09
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brain vision analyzer package bva  (brain products gmbh)
90
brain products gmbh brain vision analyzer package bva
Brain Vision Analyzer Package Bva, supplied by brain products gmbh, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/brain+vision+analyzer+software/pmc03246413-170-1-6
Average 90 stars, based on 1 article reviews
brain vision analyzer package bva - by Bioz Stars, 2026-09
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infomax ica  (InfoMax Inc)
90
InfoMax Inc infomax ica
Basic concepts of group analyses using temporal concatenation and multilevel decomposition in combination with <t>ICA</t> <t>or</t> <t>SOBI</t> . For temporal concatenation, data aggregation yields a horizontally elongated matrix on which the demixing matrix W can be estimated, assuming the same mixing process for all subjects. This, however, is not the case with multilevel decomposition since single-subject as well as group-level decomposition prior to ICA/SOBI not only reduce the number of variables, but also allow for some variability of the latent structure across subjects. Note that usually only a subset of the c*n vertically concatenated components (c = number of channels/components, n = number of subjects) enter final decomposition via ICA or SOBI.
Infomax Ica, supplied by InfoMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/infomax+ica/pmc04518160-164-6-6
Average 90 stars, based on 1 article reviews
infomax ica - by Bioz Stars, 2026-09
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wavelet analyses  (MathWorks Inc)
96
MathWorks Inc wavelet analyses
Basic concepts of group analyses using temporal concatenation and multilevel decomposition in combination with <t>ICA</t> <t>or</t> <t>SOBI</t> . For temporal concatenation, data aggregation yields a horizontally elongated matrix on which the demixing matrix W can be estimated, assuming the same mixing process for all subjects. This, however, is not the case with multilevel decomposition since single-subject as well as group-level decomposition prior to ICA/SOBI not only reduce the number of variables, but also allow for some variability of the latent structure across subjects. Note that usually only a subset of the c*n vertically concatenated components (c = number of channels/components, n = number of subjects) enter final decomposition via ICA or SOBI.
Wavelet Analyses, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/Wavelet+Toolbox/pm25962511-94-17-23
Average 96 stars, based on 1 article reviews
wavelet analyses - by Bioz Stars, 2026-09
96/100 stars
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brainvision analyzer v.2.1  (brain products gmbh)
90
brain products gmbh brainvision analyzer v.2.1
Basic concepts of group analyses using temporal concatenation and multilevel decomposition in combination with <t>ICA</t> <t>or</t> <t>SOBI</t> . For temporal concatenation, data aggregation yields a horizontally elongated matrix on which the demixing matrix W can be estimated, assuming the same mixing process for all subjects. This, however, is not the case with multilevel decomposition since single-subject as well as group-level decomposition prior to ICA/SOBI not only reduce the number of variables, but also allow for some variability of the latent structure across subjects. Note that usually only a subset of the c*n vertically concatenated components (c = number of channels/components, n = number of subjects) enter final decomposition via ICA or SOBI.
Brainvision Analyzer V.2.1, supplied by brain products gmbh, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/brain+vision+recorder/pm38849088-161-7-10
Average 90 stars, based on 1 article reviews
brainvision analyzer v.2.1 - by Bioz Stars, 2026-09
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all-mentions  (Welcony)
99
Welcony all-mentions
Basic concepts of group analyses using temporal concatenation and multilevel decomposition in combination with <t>ICA</t> <t>or</t> <t>SOBI</t> . For temporal concatenation, data aggregation yields a horizontally elongated matrix on which the demixing matrix W can be estimated, assuming the same mixing process for all subjects. This, however, is not the case with multilevel decomposition since single-subject as well as group-level decomposition prior to ICA/SOBI not only reduce the number of variables, but also allow for some variability of the latent structure across subjects. Note that usually only a subset of the c*n vertically concatenated components (c = number of channels/components, n = number of subjects) enter final decomposition via ICA or SOBI.
All Mentions, supplied by Welcony, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/all-mentions/custom%40all-mentions%4010%2E1016%2Fs0924-9338(15)30967-6
Average 99 stars, based on 1 article reviews
all-mentions - by Bioz Stars, 2026-09
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eeglab matlab package  (MathWorks Inc)
93
MathWorks Inc eeglab matlab package
Basic concepts of group analyses using temporal concatenation and multilevel decomposition in combination with <t>ICA</t> <t>or</t> <t>SOBI</t> . For temporal concatenation, data aggregation yields a horizontally elongated matrix on which the demixing matrix W can be estimated, assuming the same mixing process for all subjects. This, however, is not the case with multilevel decomposition since single-subject as well as group-level decomposition prior to ICA/SOBI not only reduce the number of variables, but also allow for some variability of the latent structure across subjects. Note that usually only a subset of the c*n vertically concatenated components (c = number of channels/components, n = number of subjects) enter final decomposition via ICA or SOBI.
Eeglab Matlab Package, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/eeglab+package+(matlab)/MATLAB+Production+Server+Client+Libraries/pm34405892-75-15-16
Average 93 stars, based on 1 article reviews
eeglab matlab package - by Bioz Stars, 2026-09
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Basic concepts of group analyses using temporal concatenation and multilevel decomposition in combination with ICA or SOBI . For temporal concatenation, data aggregation yields a horizontally elongated matrix on which the demixing matrix W can be estimated, assuming the same mixing process for all subjects. This, however, is not the case with multilevel decomposition since single-subject as well as group-level decomposition prior to ICA/SOBI not only reduce the number of variables, but also allow for some variability of the latent structure across subjects. Note that usually only a subset of the c*n vertically concatenated components (c = number of channels/components, n = number of subjects) enter final decomposition via ICA or SOBI.

Journal: Frontiers in Neuroscience

Article Title: Group-level component analyses of EEG: validation and evaluation

doi: 10.3389/fnins.2015.00254

Figure Lengend Snippet: Basic concepts of group analyses using temporal concatenation and multilevel decomposition in combination with ICA or SOBI . For temporal concatenation, data aggregation yields a horizontally elongated matrix on which the demixing matrix W can be estimated, assuming the same mixing process for all subjects. This, however, is not the case with multilevel decomposition since single-subject as well as group-level decomposition prior to ICA/SOBI not only reduce the number of variables, but also allow for some variability of the latent structure across subjects. Note that usually only a subset of the c*n vertically concatenated components (c = number of channels/components, n = number of subjects) enter final decomposition via ICA or SOBI.

Article Snippet: Notable exceptions are the implementation of Infomax ICA, SOBI, as well as functions for data filtering and plotting of EEG topographies; for these tasks, routines of the MATLAB-based open source software package EEGLAB were used (Delorme and Makeig, ).

Techniques: