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» Combining Gaussian Mixture Models
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ICASSP
2009
IEEE
14 years 3 months ago
A generalized family of parameter estimation techniques
The Extended Baum-Welch (EBW) Transformations is one of a variety of techniques to estimate parameters of Gaussian mixture models. In this paper, we provide a theoretical framewor...
Dimitri Kanevsky, Tara N. Sainath, Bhuvana Ramabha...
VTC
2007
IEEE
14 years 3 months ago
Ultra-Wideband Signal Acquisition in Non-Gaussian Noise via Successive Sampling
Abstract— Ultra-wideband (UWB) communications is envisaged to be deployed in indoor environments, where the noise distribution is decidedly non-Gaussian. A critical challenge for...
Ersen Ekrem, Mutlu Koca, Hakan Deliç
NN
2006
Springer
13 years 9 months ago
Missing data imputation through GTM as a mixture of t-distributions
The Generative Topographic Mapping (GTM) was originally conceived as a probabilistic alternative to the well-known, neural networkinspired, Self-Organizing Maps. The GTM can also ...
Alfredo Vellido
CVPR
1999
IEEE
1071views Computer Vision» more  CVPR 1999»
14 years 11 months ago
Adaptive Background Mixture Models for Real-Time Tracking
A common method for real-time segmentation of moving regions in image sequences involves "background subtraction," or thresholding the error between an estimate of the i...
Chris Stauffer, W. Eric L. Grimson
ICPR
2000
IEEE
14 years 10 months ago
Invariant Image Object Recognition Using Mixture Densities
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...
Daniel Keysers, Hermann Ney, Jörg Dahmen, Mar...