Seite - 359 - in Differential Geometrical Theory of Statistics
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Entropy2016,18, 396
In order to test theRiemannianMeanShift performance,wegenerate simple synthetic radar
clutterdata.Given250rangecells,wegenerate125cellsofgroundclutter (wind)centeredat0m·s−1,
of spectralwidth5m·s−1, towhichweadd125cellsof rainclutter, centeredat5m·s−1, of spectral
width10m·s−1. Thisclutter issampled10timesandthesegmentationisperformedoneachsimulation
(seeFigures6–8).
Figure6.Autoregressivespectra.
Figure7.Classificationresults (onecolorpercluster).
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Differential Geometrical Theory of Statistics
- Titel
- Differential Geometrical Theory of Statistics
- Autoren
- Frédéric Barbaresco
- Frank Nielsen
- Herausgeber
- MDPI
- Ort
- Basel
- Datum
- 2017
- Sprache
- englisch
- Lizenz
- CC BY-NC-ND 4.0
- ISBN
- 978-3-03842-425-3
- Abmessungen
- 17.0 x 24.4 cm
- Seiten
- 476
- Schlagwörter
- Entropy, Coding Theory, Maximum entropy, Information geometry, Computational Information Geometry, Hessian Geometry, Divergence Geometry, Information topology, Cohomology, Shape Space, Statistical physics, Thermodynamics
- Kategorien
- Naturwissenschaften Physik