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I have presented here ways in which two classical spectral-analysis
adaptive algorithms can be modified so that they are suitable to any
prediction problem. The first one, the LSL algorithm, solves
an exact least-squares problem on windows of increasing size;
its residuals don't depend on future data. The other one,
a Burg-type algorithm, uses a tapering of the residuals
to make the process adaptive, but seems less rigorous mathematically.
However, the better results are obtained by the
Burg-type algorithm, which is better stabilized than the
LSL algorithm.

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Stanford Exploration Project

1/13/1998