Abstract
We know from points (i) and (ii) of Section 1.1.2 that an inverse problem can be solved by constraining the solution either implicitly, via a prior energy U1 (x) as in Chapter 2, or explicitly by dimensionality reduction of the space containing x. The latter approach is the subject of this chapter. It is completely different from regularization with a prior energy. Dimensionality reduction has two advantages: It produces a simple exogenous model, and it is easy to handle when used as a component of a more complicated model.
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© 2003 Springer-Verlag New York, Inc.
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Chalmond, B. (2003). Parametric Spline Models. In: Modeling and Inverse Problems in Imaging Analysis. Applied Mathematical Sciences, vol 155. Springer, New York, NY. https://doi.org/10.1007/978-0-387-21662-1_3
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DOI: https://doi.org/10.1007/978-0-387-21662-1_3
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-3049-1
Online ISBN: 978-0-387-21662-1
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