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Inverse theory offers an attractive framework for designing solvers
that will enforce sparseness in the radon domain
Nichols (1994); Sacchi and Ulrych (1995).
These solvers impose focusing in the model space by adding a regularization
term in the objective function, which then penalizes small values.
This section presents two methods that address data
aliasing. One method is generally used in the time domain, and the
other is specifically designed to work in the frequency domain
Herrmann et al. (2000). For data examples of the time domain method, the
reader can refer to Guitton (2000) and
Nichols (1994). Synthetic and real data examples of
the frequency domain method follow my description of it.

** Next:** The time domain approach
** Up:** Guitton: Operator/data aliasing
** Previous:** Operator antialiasing and least-squares
Stanford Exploration Project

4/29/2001