A method for applying arithmetic coding to lossless waveform compressi
on is discussed, Arithmetic coding has been used widely in lossless te
xt compression and is known to produce compression ratios that are nea
rly optimal when the symbol table consists of an ordinary alphabet, In
lossless compression of digitized waveform data, however, if each pos
sible sample value is viewed as a ''symbol,'' the symbol table would b
e typically very large and impractical, We therefore define a symbol t
o be a certain range of possible waveform values, rather than a single
value, and develop a coding scheme on this basis. The coding scheme c
onsists of two compression stages, The first stage is lossless linear
prediction, which removes coherent components from a digitized wavefor
m and produces a residue sequence that is assumed to have a white spec
trum and a Gaussian amplitude distribution, The prediction is lossless
in the sense that the original digitized waveform can be recovered by
processing the residue sequence, The second stage, which is the subje
ct of this paper, is arithmetic coding used as just described, A formu
la for selecting ranges of waveform values is provided, Experiments wi
th seismic and speech waveforms that produce near-optimal results are
included.