| DUALCOV | |
Dual representation of covariance matrix.
Synopsis:
Z=dualcov(num_data)
Z=dualcov(labels, y)
Description:
This function computes a matrix Z [num_data x num_data] which allows
to express the sample covariance matrix of data sample X [dim x num_data]
in terms of dot products.
Z = dualcov(num_data) computes a matrix Z [num_data x num_data] such that
cov(X',1) = X*Z*X'.
m = dualcov(labels,y) computes a matrix Z [length(y) x length(y)] such that
cov(X(:,find(labels==y))',1) = X*Z*X',
where labels [1 x num_data] is a vector of data labels and y [1x1]
is a label od class which covariance metrix is to be computed.
Example:
Unlabeled data:
data = load('riply_trn');
ca = cov( data.X', 1)
cb = data.X*dualcov(size(data.X,2))*data.X'
Labeled data:
data = load('riply_trn');
ca1 = cov( data.X(:,find(data.y==1))',1)
cb1 = data.X*dualcov(data.y,1)*data.X'
ca2 = cov( data.X(:,find(data.y==2))',1)
cb2 = data.X*dualcov(data.y,2)*data.X'
See also
DUALMEAN.
About: Statistical Pattern Recognition Toolbox
(C) 1999-2003, Written by Vojtech Franc and Vaclav Hlavac
Czech Technical University Prague
Faculty of Electrical Engineering
Center for Machine Perception
Modifications:
16-may-2004, VF
14-may-2004, VF
22-Jan-2003, VF
22-May-2001, V. Franc, created