Sobre separação cega de fontes : proposições e analise de estrategias para processamento multi-usuario

Orientadores: João Marcos Travassos Romano, Francisco Rodrigo Porto CavalcantiTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoResumo: Esta tese é dedicada ao estudo de tecnicas de separação cega de fontes aplicadas ao contexto de processamento multiusuario em comunicações digitais. Utilizando estrategias de estimação da função de densidade de probabilidade (fdp), são propostos dois metodos de processamento multiusuario que permitem recuperar os sinais transmitidos pela medida de similaridade de Kullback-Leibler entre a fdp dos sinais a saida do dispositivo de separação e um modelo parametrico que contem as caracteristicas dos sinais transmitidos. Alem desta medida de similaridade, são empregados diferentes metodos que garantem a descorrelação entre as estimativas das fontes de tal forma que os sinais recuperados sejam provenientes de diferentes fontes. E ainda realizada a analise de convergencia dos metodos e suas equivalencias com tecnicas classicas resultando em algumas importantes relações entre criterios cegos e supervisionados, tais como o criterio proposto e o criterio de maxima a posteriori. Estes novos metodos aliam a capacidade de recuperação da informação uma baixa complexidade computacional. A proposição de metodos baseados na estimativa da fdp permitiu a realização de um estudo sobre o impacto das estatisticas de ordem superior em algoritmos adaptativos para separação cega de fontes. A utilização da expansão da fdp em series ortonormais permite avaliar atraves dos cumulantes a dinamica de um processo de separação de fontes. Para tratar com problemas de comunicação digital e proposta uma nova serie ortonormal, desenvolvida em torno de uma função de densidade de probabilidade dada por um somatorio de gaussianas. Esta serie e utilizada para evidenciar as diferenças em relação ao desempenho em tempo real ao se reter mais estatisticas de ordem superior. Simulações computacionais são realizadas para evidenciar o desempenho das propostas frente a tecnicas conhecidas da literatura em varias situações de necessidade de alguma estrategia de recuperação de sinaisAbstract: This thesis is devoted to study blind source separation techniques applied to multiuser processing in digital communications. Using probability density function (pdf) estimation strategies, two multiuser processing methods are proposed. They aim for recovering transmitted signal by using the Kullback-Leibler similarity measure between the signals pdf and a parametric model that contains the signals characteristics. Besides the similarity measure, different methods are employed to guarantee the decorrelation of the sources estimates, providing that the recovered signals origin from different sources. The convergence analysis of the methods as well as their equivalences with classical techniques are presented, resulting on important relationships between blind and supervised criteria such as the proposal and the maximum a posteriori one. Those new methods have a good trade-off between the recovering ability and computational complexity. The proposal os pdf estimation-based methods had allowed the investigation on the impact of higher order statistics on adaptive algorithms for blind source separation. Using pdf orthonormal series expansion we are able to evaluate through cumulants the dynamics of a source separation process. To be able to deal with digital communication signals, a new orthonormal series expansion is proposed. Such expansion is developed in terms of a Gaussian mixture pdf. This new expansion is used to evaluate the differences in real time processing when we retain more higher order statistics. Computational simulations are carried out to stress the performance of the proposals, faced to well known techniques reported in the literature, under the situations where a recovering signal strategy is required.DoutoradoTelecomunicações e TelemáticaDoutor em Engenharia Elétric

An ensemble learning approach for the classification of remote sensing scenes based on covariance pooling of CNN features

International audienceThis paper aims at presenting a novel ensemble learning approach based on the concept of covariance pooling of CNN features issued from a pretrained model. Starting from a supervised classification algorithm, named multilayer stacked covariance pooling (MSCP), which exploits simultaneously second order statistics and deep learning features, we propose an alternative strategy which employs an ensemble learning approach among the stacked convolutional feature maps. The aggregation of multiple learning algorithm decisions, produced by different stacked subsets, permits to obtain a better predictive classification performance. An application for the classification of large scale remote sensing images is next proposed. The experimental results, conducted on two challenging datasets, namely UC Merced and AID datasets, improve the classification accuracy while maintaining a low computation time. This confirms, besides the interest of exploiting second order statistics, the benefit of adopting an ensemble learning approach

A Unified Framework for HS-UAV NOMA Networks: Performance Analysis and Location Optimization

In this paper, we propose a unified framework for hybrid satellite/unmanned aerial vehicle (HS-UAV) terrestrial non-orthogonal multiple access (NOMA) networks, where satellite aims to communicate with ground users with the aid of a decode-forward (DF) UAV relay by using NOMA protocol. All users are randomly deployed to follow a homogeneous Poisson point process (PPP), which is modeled by the stochastic geometry approach. To reap the benefits of satellite and UAV, the links of both satellite-to-UAV and UAV-to-ground user are assumed to experience Rician fading. More practically, we assume that perfect channel state information (CSI) is infeasible at the receiver, as well as the distance-determined path-loss. To characterize the performance of the proposed framework, we derive analytical approximate closed-form expressions of the outage probability (OP) for the far user and the near user under the condition of imperfect CSI. Also, the system throughput under delay-limited transmission mode is evaluated and discussed. In order to obtain more insights, the asymptotic behavior is explored in the high signal-to-noise ratio (SNR) region and the diversity orders are obtained and discussed. To further improve the system performance, based on the derived approximations, we optimize the location of the UAV to maximize the sum rate by minimizing the average distance between the UAV and users. The simulated numerical results show that: i) there are error floors for the far and the near users due to the channel estimation error; ii) the outage probability decreases as the Rician factor K increasing, and iii) the outage performance and system throughput performance can be further improved considerably by carefully selecting the location of the UAV

Metabolism of a Lipid Nanoemulsion Resembling Low-Density Lipoprotein in Patients with Grade III Obesity

INTRODUCTION: Obesity increases triglyceride levels and decreases high-density lipoprotein concentrations in plasma. Artificial emulsions resembling lipidic plasma lipoprotein structures have been used to evaluate low-density lipoprotein metabolism. In grade III obesity, low density lipoprotein metabolism is poorly understood. OBJECTIVE: To evaluate the kinetics with which a cholesterol-rich emulsion (called a low-density emulsion) binds to low-density lipoprotein receptors in a group of patients with grade III obesity by the fractional clearance rate. METHODS: A low-density emulsion was labeled with [14C]-cholesterol ester and [³H]-triglycerides and injected intravenously into ten normolipidemic non-diabetic patients with grade III obesity [body mass index higher than 40 kg/m²] and into ten non-obese healthy controls. Blood samples were collected over 24 hours to determine the plasma decay curve and to calculate the fractional clearance rate. RESULTS: There was no difference regarding plasma levels of total cholesterol or low-density lipoprotein cholesterol between the two groups. The fractional clearance rate of triglycerides was 0.086 ± 0.044 in the obese group and 0.122 ± 0.026 in the controls (p = 0.040), and the fractional clearance rate of cholesterol ester (h-1) was 0.052 ± 0.021 in the obese subjects and 0.058 ± 0.015 (p = 0.971) in the controls. CONCLUSION: Grade III obese subjects exhibited normal low-density lipoprotein removal from plasma as tested by the nanoemulsion method, but triglyceride removal was slower