function?features?=?extractCSPFeatures（EEGSignals?CSPMatrix?nbFilterPairs）

%extract?features?from?an?EEG?data?set?using?the?Common?Spatial?Patterns?（CSP）?algorithm
%
%Input:
%EEGSignals:?the?EEGSignals?from?which?extracting?the?CSP?features.?These?signals
%are?a?structure?such?that:
%???EEGSignals.x:?the?EEG?signals?as?a?[Ns?*?Nc?*?Nt]?Matrix?where
%???????Ns:?number?of?EEG?samples?per?trial
%???????Nc:?number?of?channels?（EEG?electrodes）
%???????nT:?number?of?trials
%???EEGSignals.y:?a?[1?*?Nt]?vector?containing?the?class?labels?for?each?trial
%???EEGSignals.s:?the?sampling?frequency?（in?Hz）
%CSPMatrix:?the?CSP?projection?matrix?learnt?previously?（see?function?learnCSP）
%nbFilterPairs:?number?of?pairs?of?CSP?filters?to?be?used.?The?number?of
%???features?extracted?will?be?twice?the?value?of?this?parameter.?The
%???filters?selected?are?the?one?corresponding?to?the?lowest?and?highest
%???eigenvalues
%
%Output:
%features:?the?features?extracted?from?this?EEG?data?set?
%???as?a?[Nt?*?（nbFilterPairs*2?+?1）]?matrix?with?the?class?labels?as?the
%???last?column???

%initializations
nbTrials?=?size（EEGSignals.x3）;
features?=?zeros（nbTrials?2*nbFilterPairs+1）;
Filter?=?CSPMatrix（[1:nbFilterPairs?（end-nbFilterPairs+1）:end]:）;

%extracting?the?CSP?features?from?each?trial
for?t=1:nbTrials????
????%projecting?the?data?onto?the?CSP?filters????
????projectedTrial?=?Filter?*?EEGSignals.x（::t）‘;????
????
????%generating?the?features?as?the?log?variance?of?the?projected?signals
????variances?=?var（projectedTrial02）;????
????for?f=1:length（variances）
????????features（tf）?=?log（variances（f））;
????end
????features（tend）?=?EEGSignals.y（t）;????
end

?屬性????????????大小?????日期????時(shí)間???名稱
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?????文件???????1708??2018-04-04?16:03??extractCSPFeatures.m

?????文件???????2015??2018-03-29?10:30??learnCSP.m

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?????????????????3723????????????????????2