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TSP
2010
14 years 4 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
14 years 9 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
14 years 4 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
85
Voted
ICASSP
2010
IEEE
14 years 9 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
14 years 1 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...