wolffd@0: wolffd@0:
wolffd@0:wolffd@0: n2 = mdndist2(mixparams, t) wolffd@0:wolffd@0: wolffd@0: wolffd@0:
n2 = mdndist2(mixparams, t)
takes takes the centres of the Gaussian
wolffd@0: contained in
wolffd@0: mixparams
and the target data matrix, t
, and computes the squared
wolffd@0: Euclidean distance between them. If t
has m
rows and n
wolffd@0: columns, then the centres
field in
wolffd@0: the mixparams
structure should have m
rows and
wolffd@0: n*mixparams.ncentres
columns: the centres in each row relate to
wolffd@0: the corresponding row in t
.
wolffd@0: The result has m
rows and mixparams.ncentres
columns.
wolffd@0: The i, j
th entry is the
wolffd@0: squared distance from the i
th row of x
to the j
th
wolffd@0: centre in the i
th row of mixparams.centres
.
wolffd@0:
wolffd@0: mdnfwd
, mdnprob
Copyright (c) Ian T Nabney (1996-9) wolffd@0:
David J Evans (1998) wolffd@0: wolffd@0: wolffd@0: