Waveform Modeling<A NAME=ssmodel> </A>

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Waveform Modeling 

Compression is achieved by building a predictive model of the waveform (a good introduction for speech is Jayant and Noll [2]). An established model for a wide variety of waveforms is that of an autoregressive model, also known as linear predictive coding (LPC). Here the predicted waveform is a linear combination of past samples:


The coded signal, , is the difference between the estimate of the linear predictor, and the speech signal, .


However, many waveforms of interest are not stationary, that is the best values for the coefficients of the predictor, , vary from one section of the waveform to another. It is often reasonable to assume that the signal is pseudo-stationary, i.e. there exists a time-span over which reasonable values for the linear predictor can be found. Thus the three main stages in the coding process are blocking, predictive modelling, and residual coding.

Tony Robinson: ajr4@cam.ac.uk