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In Chapter we learned that least squares residuals
should be IID (Independent, Identically Distributed)
which in practical terms means in both Fourier space and physical
space they should have a uniform variance.
Further, not only should residuals have the IID property,
but we should choose a preconditioning transformation
so that our unknowns have the same IID nature.
It is easy enough to achieve flattening in physical space
by means of weighting functions.
Here we see that Prediction-error filters (PEFs) enable
us to flatten in fourier space.
PEFs transform signals and images to whiteness.
Residuals and preconditioned models should be white.