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TSP
2008
105views more  TSP 2008»
13 years 7 months ago
Semi-Supervised Linear Spectral Unmixing Using a Hierarchical Bayesian Model for Hyperspectral Imagery
This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linea...
Nicolas Dobigeon, Jean-Yves Tourneret, Chein-I Cha...
JCNS
1998
134views more  JCNS 1998»
13 years 7 months ago
Analytical and Simulation Results for Stochastic Fitzhugh-Nagumo Neurons and Neural Networks
An analytical approach is presented for determining the response of a neuron or of the activity in a network of connected neurons, represented by systems of nonlinear ordinary stoc...
Henry C. Tuckwell, Roger Rodriguez
DSP
2008
13 years 7 months ago
Empirical Bayes linear regression with unknown model order
We study maximum a posteriori probability model order selection for linear regression models, assuming Gaussian distributed noise and coefficient vectors. For the same data model,...
Yngve Selén, Erik G. Larsson
ICIP
2005
IEEE
14 years 1 months ago
Two-step variance-adaptive image denoising
Abstract— In this paper, we describe a two-step varianceadaptive method for image denoising based on a statistical model of the coefficients of balanced multiwavelet transform. ...
Lahouari Ghouti, Ahmed Bouridane
ICASSP
2011
IEEE
12 years 11 months ago
Impulsive interference mitigation in ad hoc networks based on alpha-stable modeling and particle filtering
In this paper, we tackle the problem of interference mitigation in ad hoc networks. In such context, the multiple access interference (MAI) is known to be of an impulsive nature. ...
Nouha Jaoua, Emmanuel Duflos, Philippe Vanheeghe, ...