  This paper describes some applications of an incremental implementation of
the principal component analysis (PCA). The algorithm updates the
transformation coefficients matrix on-line for each new sample, without the
need to keep all the samples in memory. The algorithm is formally equivalent to
the usual batch version, in the sense that given a sample set the
transformation coefficients at the end of the process are the same. The
implications of applying the PCA in real time are discussed with the help of
data analysis examples. In particular we focus on the problem of the continuity
of the PCs during an on-line analysis.
