Zobrazeno 1 - 10
of 109
pro vyhledávání: '"Fleury, Bernard Henri"'
A source traffic model for machine-to-machine communications is presented in this paper. We consider a model in which devices operate in a regular mode until they are triggered into an alarm mode by an alarm event. The positions of devices and events
Externí odkaz:
http://arxiv.org/abs/1709.00867
A number of recent works have proposed to solve the line spectral estimation problem by applying off-the-grid extensions of sparse estimation techniques. These methods are preferable over classical line spectral estimation algorithms because they inh
Externí odkaz:
http://arxiv.org/abs/1705.06073
In this paper, we address the fundamental problem of line spectral estimation in a Bayesian framework. We target model order and parameter estimation via variational inference in a probabilistic model in which the frequencies are continuous-valued, i
Externí odkaz:
http://arxiv.org/abs/1604.03744
Autor:
Zhang, Chuanzong, Wang, Zhongyong, Manchón, Carles Navarro, Sun, Peng, Guo, Qinghua, Fleury, Bernard Henri
Publikováno v:
IEEE Signal Processing Letters, vol. 23, No. 9, pp. 1216 -1220, Sept. 2016
This paper deals with turbo-equalization for coded data transmission over intersymbol interference (ISI) channels. We propose a message-passing algorithm that uses the expectation-propagation rule to convert messages passed from the demodulator-decod
Externí odkaz:
http://arxiv.org/abs/1603.04142
We propose a framework for the derivation and evaluation of distributed iterative algorithms for receiver cooperation in interference-limited wireless systems. Our approach views the processing within and collaboration between receivers as the soluti
Externí odkaz:
http://arxiv.org/abs/1204.3742
Existing methods for sparse channel estimation typically provide an estimate computed as the solution maximizing an objective function defined as the sum of the log-likelihood function and a penalization term proportional to the l1-norm of the parame
Externí odkaz:
http://arxiv.org/abs/1204.0656
Autor:
Badiu, Mihai-Alin, Kirkelund, Gunvor Elisabeth, Manchón, Carles Navarro, Riegler, Erwin, Fleury, Bernard Henri
We design iterative receiver schemes for a generic wireless communication system by treating channel estimation and information decoding as an inference problem in graphical models. We introduce a recently proposed inference framework that combines b
Externí odkaz:
http://arxiv.org/abs/1202.1467
Autor:
Pedersen, Niels Lovmand, Manchón, Carles Navarro, Badiu, Mihai-Alin, Shutin, Dmitriy, Fleury, Bernard Henri
Publikováno v:
Signal Processing 115 (2015) 94-109
In sparse Bayesian learning (SBL), Gaussian scale mixtures (GSMs) have been used to model sparsity-inducing priors that realize a class of concave penalty functions for the regression task in real-valued signal models. Motivated by the relative scarc
Externí odkaz:
http://arxiv.org/abs/1108.4324
Autor:
Pedersen, Niels Lovmand, Navarro Manchón, Carles, Badiu, Mihai-Alin, Shutin, Dmitriy, Fleury, Bernard Henri
Publikováno v:
In Signal Processing October 2015 115:94-109
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