The authors proposed a method for decoding interpolatively encoded data. This class of coding scheme achieves higher estimation gain and are symmetric with respect to time which makes them a good candidate for storage application. They showed that different trade-off parameters are involved and investigated their relationships. These parameters are estimation gain, delay experienced by the encoder and the decoder and end-to-end signal-to-noise ratio. They also showed the implementation and the effect of incorporating quantizers in the circuits. Specifically, they investigated two extreme open and closed loop architectures and compared their performances. Generalization of the above algorithm to noise feedback coding can be achieved easily.<<ETX>>
[1]
Benjamin Friedlander,et al.
Least squares algorithms for adaptive linear-phase filtering
,
1982
.
[2]
Peter No,et al.
Digital Coding of Waveforms
,
1986
.
[3]
Bernard C. Picinbono,et al.
Some properties of prediction and interpolation errors
,
1988,
IEEE Trans. Acoust. Speech Signal Process..
[4]
A.K. Jain,et al.
Advances in mathematical models for image processing
,
1981,
Proceedings of the IEEE.
[5]
A. N. Kolmogorov,et al.
Interpolation and extrapolation of stationary random sequences.
,
1962
.