  This paper addresses the problem of coding a continuous random source
correlated with another source which is only available at the decoder. The
proposed approach is based on the extension of the channel coding concept of
syndrome from the discrete into the continuous domain. If the correlation
between the sources can be described by an additive Gaussian backward channel
and capacity-achieving linear codes are employed, it is shown that the
performance of the system is asymptotically close to the Wyner-Ziv bound. Even
if such an additive channel is not Gaussian, the design procedure can fit the
desired correlation and transmission rate. Experiments based on trellis-coded
quantization show that the proposed system achieves a performance within 3-4 dB
of the theoretical bound in the 0.5-3 bit/sample rate range for any Gaussian
correlation, with a reasonable computational complexity.
