Adjustment of nonuniform sampling locations in spatial data sets.

This article describes a procedure for adjusting sampling locations in one spatially discretized data set to those in another when the value differences between these sets are mainly caused by the sampling intervals that locally lengthen and shorten. This adjustment is formulated into an optimizatio...

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Publicado no:	IEEE Signal processing magazine 21, 3 (2004).
Autor principal:	Kamiyama, M.
Formato:	Artigo
Idioma:	English
Assuntos:	Bayesian framework. Dynamic programming. Maximum a posteriori estimate. Maximum likelihood procedure. Nonlinear filtering. Nonuniform sampling location adjustment. Optimization. Rail geometry data sets. Spatially discretized data set. State-space model.