LPC (Linear Predictive Coding) is a filtering technique whereby the value
of a sample is computed ("predicted") as a weighted sum of the previous
samples. The weights assigned to each previous sample are the coefficients
of the filter, and the number of previous samples considered the order of
the filter.x2 = x1 - x0 is an example of such a filter, of order 2, and where the coefficients are 1 and -1. If you have the values of x0 and x1, you are able to predict the value of x2, knowing only the order of the filter, and the coefficients, then that of x3 from x2 and x1, and so on... The higher the order of the filter, the more complexity you are able to match at the signal level. For more, there are plenty of reference on the internet (you can start there : http://en.wikipedia.org/wiki/Linear_prediction) Best regards, Pyt. On Thu, Jun 14, 2012 at 11:28 PM, Martin Leese < martin.le...@stanfordalumni.org> wrote: > [...] > I have not attempted to explain what the LPC > order actually is because I do not understand > it well enough > >
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