class notes

Ex01_testPCA.m

@@ -1,4 +1,5 @@
-% Principal component analysis
+%Zahara Wang zahara.wang@emory.edu
+%Principal component analysis
 %
 % BMI500 Course
 % Lecture:  An Introduction to Blind Source Separation and Independent Component Analysis
@@ -32,6 +33,9 @@
     otherwise
         error('unknown example');
 end
+x_demeaned = x - mean(x,2)*ones(1,size(x,2));
+Cx =  cov(x_demeaned');
+[V, D] = eig(Cx, 'vector');
 
 N = size(x, 1); % The number of channels
 T = size(x, 2); % The number of samples per channel

Ex02_testEigenAnalysisPowerMethod.m

@@ -1,3 +1,4 @@
+%Zahara Wang zahara.wang@emory.edu
 % The power method for eigenvalue decomposition
 %
 % BMI500 Course
@@ -24,3 +25,11 @@
 % Cx = x * x';
 Cx = cov(x');
 
+[V,D] = eig(Cx)
+
+Itr = 100;
+
+v0 = rand(N,1);
+v1 = EigenAnalysisPowerMethod(Cx, v0, Itr);
+scale1 = (Cx*v1) ./v1;
+lambda1 = mean(scale1);

Ex03_testICAmethods.m

@@ -1,3 +1,4 @@
+%Zahara Wang zahara.wang@emory.edu
 % Independent component analysis using classical methods
 %
 % BMI500 Course
@@ -46,3 +47,13 @@
 N = size(x, 1); % The number of channels
 T = size(x, 2); % The number of samples per channel
 
+approach = "symm"; 
+g = "tanh";
+lastEigfastica = N; 
+numOfIC = N; 
+interactivePCA = 'off';
+[s_fastica, A_fastica, W_fastica] = fastica(x, 'approach', approach, ...
+        'g', g, 'lastEig', lastEigfastica, 'numOfIC', numOfIC, ...
+        'interactivePCA', interactivePCA);
+
+Cs = cov(s_fastica');

Ex04_testEOGArtifactRemoval.m

@@ -1,3 +1,4 @@
+%Zahara Wang zahara.wang@emory.edu
 % Removing EOG artifacts from EEG signals
 %
 % BMI500 Course

Ex05_testFetalECGExtraction.m

@@ -1,3 +1,4 @@
+%Zahara Wang zahara.wang@emory.edu
 % Extracting fetal ECG signals using various ICA algorithms
 %
 % BMI500 Course