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TSP
2010
12 years 11 months ago
Estimating multiple frequency-hopping signal parameters via sparse linear regression
Abstract--Frequency hopping (FH) signals have well-documented merits for commercial and military applications due to their near-far resistance and robustness to jamming. Estimating...
Daniele Angelosante, Georgios B. Giannakis, Nichol...
ICASSP
2010
IEEE
13 years 4 months ago
Multiple frequency-hopping signal estimation via sparse regression
Frequency hopping (FH) signals have well-documented merits for commercial and military applications due to their near-far resistance and robustness to jamming. Estimating FH signa...
Daniele Angelosante, Georgios B. Giannakis, Nichol...
TSP
2010
12 years 11 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
ICASSP
2010
IEEE
13 years 4 months ago
Distributed Lasso for in-network linear regression
The least-absolute shrinkage and selection operator (Lasso) is a popular tool for joint estimation and continuous variable selection, especially well-suited for the under-determin...
Juan Andrés Bazerque, Gonzalo Mateos, Georg...
ICASSP
2011
IEEE
12 years 8 months ago
A reversible jump MCMC algorithm for Bayesian curve fitting by using smooth transition regression models
This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear...
Matthieu Sanquer, Florent Chatelain, Mabrouka El-G...