<--- Back to Details
First PageDocument Content
De Bilt / Royal Netherlands Meteorological Institute / LIDAR / Parametrization / KNMI / Atmospheric sciences / Meteorology / Air dispersion modeling
Date: 2011-10-03 04:11:44
De Bilt
Royal Netherlands Meteorological Institute
LIDAR
Parametrization
KNMI
Atmospheric sciences
Meteorology
Air dispersion modeling

Microsoft Word - 2010_Minutes_meeting_DeBilt_June.doc

Add to Reading List

Source URL: www.euclipse.eu

Download Document from Source Website

File Size: 57,05 KB

Share Document on Facebook

Similar Documents

b (after Vogan) A parametrization of K Peter E. Trapa Notes from an AIM workshop, July 2004

DocID: 1vd7M - View Document

Ann Inst Stat Math:787–803 DOIs10463x Approximate theory-aided robust efficient factorial fractions under baseline parametrization Rahul Mukerjee · S. Huda

DocID: 1rye2 - View Document

Test design under voluntary participation Supplementary material Frank Rosar University of Bonn April 27, Parametrization of HARA utility

DocID: 1relc - View Document

Interpolation / Numerical analysis / B-spline / Flat spline / Cubic Hermite spline / Spline / Control point / Linear interpolation / Shape optimization / Finite element method / Mesh generation / Computer representation of surfaces

Integrated geometry parametrization and grid movement using B-spline meshes Jason E. Hicken∗ and David W. Zingg †

DocID: 1qRkm - View Document

Machine learning / Cybernetics / Learning / Manifold / Cognition / Dimension reduction / Multivariate statistics / Cognitive science / Nonlinear dimensionality reduction

Manifold learning algorithms aim to recover the underlying lowdimensional parametrization of the data using either local or global features. It is however widely recognized that the low dimensional parametrizations will

DocID: 1qwmo - View Document