Thread Subject: [MxN] for principle component analysis (PCA)

I am trying to create a matrix [MxN] for principle component analysis.
My problem is that my waveforms do not all have the same vector length
N, there is a difference of 15 to 100 data points. I am unsure what
type of algorithm to use, or how in general to adjust the waveforms to
the same vector length N.

I know that this will change the frequency of the signal slightly but
I am not so concerned the, with that slight change. I am looking for
identifying features over one rotation of the device one rotation may
take a few milliseconds longer so the waveform vector has more data
points. I need those vectors to contain the same number of points.

A thought that I had was to add zeros to the end of each waveform
making them all length N but I am unsure how that would effect PCA, if
any one knows that would also be helpful information.

Nate

hi
i think it is better for you to start with this paper: (A
tutorial on Principal Components Analysis by Lindsay I
Smith) you can found it in the internet