In this thesis, we consider first the problem of low dimensional signal subspace estimation in a Bayesian context. We focus on compound Gaussian signals embedded in white Gaussian noise, which is a realistic modeling for various array processing applications. Following the Bayesian framework, we derive algorithms to compute both the maximum a poste...
In this paper, we consider the problem of low dimensional signal subspace estimation in a Bayesian con- text. We focus on compound Gaussian signals embedded in white Gaussian noise, which is a realistic modeling for various array processing applications. Following the Bayesian framework, we derive two algorithms to compute the maximum a posteriori ...
Les problèmes d'optimisation continue sont nombreux, en économie, en traitement de signal, en réseaux de neurones, etc. L'une des solutions les plus connues et les plus employées est l'algorithme évolutionnaire, métaheuristique basée sur les théories de l'évolution qui emprunte des mécanismes stochastiques et qui a surtout montré de bonnes performa...
La géolocalisation indoor en temps réel a largement été étudiée ces dernières années, et de nombreuses applications y sont associées. Une estimation en temps différé de la trajectoire présente également un certain intérêt. La géolocalisation indoor en temps différé permet par exemple de développer des approches de type crowdsourcing qui tirent prof...
To be efficient and reach the best solution, evolutionary algorithms (EAs) are composed of three evolutionary operators: selection, crossover and mutation. Nevertheless, there is no established rule to choose them from a large panel of operators available in the literature.In this paper, a Maximum A Posteriori (MAP) principle based rule is proposed...
Published in Wireless Networks
Channel state information is very important in cooperative communication for performance improvement or signal demodulation. Previous works on channel state information estimation mainly focus on least squares and minimum mean squared error estimators. In this work, several new maximum likelihood and maximum a posteriori estimators for the cooperat...
Published in Magnetic resonance imaging
In recent years, several efforts have been done for producing Magnetic Resonance Image scanner with higher magnetic field strength mainly for increasing the Signal to Noise Ratio and the Contrast to Noise Ratio of the acquired images. However, denoising methodologies still play an important role for achieving images neatness. Several denoising algo...
Published in BioMedical Engineering OnLine
BackgroundWithin this manuscript a noise filtering technique for magnetic resonance image stack is presented. Magnetic resonance images are usually affected by artifacts and noise due to several reasons. Several denoising approaches have been proposed in literature, with different trade-off between computational complexity, regularization and noise...
Published in Magnetic resonance imaging
In recent years, several efforts have been done for producing Magnetic Resonance Image scanner with higher magnetic field strength mainly for increasing the Signal to Noise Ratio and the Contrast to Noise Ratio of the acquired images. However, denoising methodologies still play an important role for achieving images neatness. Several denoising algo...
Published in Annals of Telecommunications
With the rapid development of a cloud computing network, the network security has been a terrible problem when it provides much more services and applications. Network traffic modeling and analysis is significantly crucial to detect some lawless activities such as DDoS, virus and worms, and so on. Meanwhile, it is a common approach for acquiring a ...
