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» Parametric interpolation using sampled data
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ICML
1999
IEEE
14 years 8 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
VIS
2005
IEEE
110views Visualization» more  VIS 2005»
14 years 8 months ago
Prefiltered Gaussian Reconstruction for High-Quality Rendering of Volumetric Data sampled on a Body-Centered Cubic Grid
In this paper a novel high-quality reconstruction scheme is presented. Although our method is mainly proposed to reconstruct volumetric data sampled on an optimal Body-Centered Cu...
Balázs Csébfalvi
CORR
2011
Springer
194views Education» more  CORR 2011»
12 years 11 months ago
Efficient Maximum Likelihood Estimation of a 2-D Complex Sinusoidal Based on Barycentric Interpolation
This paper presents an efficient method to compute the maximum likelihood (ML) estimation of the parameters of a complex 2-D sinusoidal, with the complexity order of the FFT. The...
J. Selva
ICC
2007
IEEE
128views Communications» more  ICC 2007»
14 years 1 months ago
Parametric Channel Estimation in Reuse-1 OFDM Systems
— We propose an improved channel estimator for reuse-1 orthogonal frequency division multiplexing (OFDM) cellular systems1 . The proposed channel estimation technique exploits de...
M. R. Raghavendra, Srikrishna Bhashyam, Krishnamur...
VLSM
2005
Springer
14 years 25 days ago
A C1 Globally Interpolatory Spline of Arbitrary Topology
Converting point samples and/or triangular meshes to a more compact spline representation for arbitrarily topology is both desirable and necessary for computer vision and computer ...
Ying He 0001, Miao Jin, Xianfeng Gu, Hong Qin