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Pattern clustering based on noise modeling in wavelet space

✍ Scribed by Fionn Murtagh; Jean-Luc Starck

Publisher
Elsevier Science
Year
1998
Tongue
English
Weight
797 KB
Volume
31
Category
Article
ISSN
0031-3203

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✦ Synopsis

We describe an effective approach to object or feature detection in point patterns via noise modeling. This is based on use of a redundant or non-pyramidal wavelet transform. Noise modeling is based on a Poisson process. We illustrate this new method with a range of examples. We use the close relationship between image (pixelated) and point representations to achieve the result of a clustering method with constant-time computational cost.

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## Abstract The UTD method with the source on convex surface which is usually used in the analysis and design of antennas especially conformal arrays on electrically large platforms is studied in this article where NURBS is introduced as way of modeling. Together with the information from ray‐traci