996 resultados para correlated sources
Resumo:
In this paper we address the problem of transmission of correlated sources over a fading multiple access channel (MAC). We provide sufficient conditions for transmission with given distortions. Next these conditions are specialized to a Gaussian MAC (GMAC). Transmission schemes for discrete and Gaussian sources over a fading GMAC are considered. Various power allocation strategies are also compared.
Resumo:
In this paper we address the problem of distributed transmission of functions of correlated sources over a fast fading multiple access channel (MAC). This is a basic building block in a hierarchical sensor network used in estimating a random field where the cluster head is interested only in estimating a function of the observations. The observations are transmitted to the cluster head through a fast fading MAC. We provide sufficient conditions for lossy transmission when the encoders and decoders are provided with partial information about the channel state. Furthermore signal side information maybe available at the encoders and the decoder. Various previous studies are shown as special cases. Efficient joint-source channel coding schemes are discussed for transmission of discrete and continuous alphabet sources to recover function values.
Resumo:
In this paper we address the problem of transmission of correlated sources over a fading multiple access channel (MAC). We provide sufficient conditions for transmission with given distortions. Next these conditions are specialized to a Gaussian MAC (GMAC). Transmission schemes for discrete and Gaussian sources over a fading GMAC are considered. Various power allocation strategies are also compared. Keywords: Fading MAC, Power allocation, Random TDMA, Amplify and Forward, Correlated sources.
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This paper studies the problem of blind source separation (BSS) from instantaneous mixtures with the assumption that the source signals are mutually correlated.We propose a novel approach to BSS by using precoders in transmitters.We show that if the precoders are properly designed, some cross-correlation coefficients of the coded signals can be forced to be zero at certain time lags. Then, the unique correlation properties of the coded signals can be exploited in receiver to achieve source separation. Based on the proposed precoders, a subspace-based algorithm is derived for the blind separation of mutually correlated sources. The effectiveness of the algorithm is illustrated by simulation examples.
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Distributed compressed sensing exploits information redundancy, inbuilt in multi-signal ensembles with interas well as intra-signal correlations, to reconstruct undersampled signals. In this paper we revisit this problem, albeit from a different perspective, of taking streaming data, from several correlated sources, as input to a real time system which, without any a priori information, incrementally learns and admits each source into the system.
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In this paper, we address the problem of blind separation of spatially correlated signals, which is encountered in some emerging applications, e.g., distributed wireless sensor networks and wireless surveillance systems. We preprocess the source signals in transmitters prior to transmission. Specifically, the source signals are first filtered by a set of properly designed precoders and then the coded signals are transmitted. On the receiving side, the Z-domain features of the precoders are exploited to separate the coded signals, from which the source signals are recovered. Based on the proposed precoders, a closed-form algorithm is derived to estimate the coded signals and the source signals. Unlike traditional blind source separation approaches, the proposed method does not require the source signals to be uncorrelated, sparse, or nonnegative. Compared with the existing precoder-based approach, the new method uses precoders with much lower order, which reduces the delay in data transmission and is easier to implement in practice.
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This paper presents a projection pursuit (PP) based method for blind separation of nonnegative sources. First, the available observation matrix is mapped to construct a new mixing model, in which the inaccessible source matrix is normalized to be column-sum-to-1. Then, the PP method is proposed to solve this new model, where the mixing matrix is estimated column by column through tracing the projections to the mapped observations in specified directions, which leads to the recovery of the sources. The proposed method is much faster than Chan's method, which has similar assumptions to ours, due to the usage of optimal projection. It is also more advantageous in separating cross-correlated sources than the independence- and uncorrelation-based methods, as it does not employ any statistical information of the sources. Furthermore, the new method does not require the mixing matrix to be nonnegative. Simulation results demonstrate the superior performance of our method.
Resumo:
This paper deals with blind separation of spatially correlated signals mixed by an instantaneous system. Taking advantage of the fact that the source signals are accessible in some man-made systems such as wireless communication systems, we preprocess the source signals in transmitters by a set of properly designed first-order precoders and then the coded signals are transmitted. At the receiving side, information about the precoders are utilized to perform signal separation. Compared with the existing precoder-based methods, the new method only employs the simplest first-order precoders, which reduces the delay in data transmission and is easier to implement in practical applications.
Resumo:
This paper presents a convex geometry (CG)-based method for blind separation of nonnegative sources. First, the unaccessible source matrix is normalized to be column-sum-to-one by mapping the available observation matrix. Then, its zero-samples are found by searching the facets of the convex hull spanned by the mapped observations. Considering these zero-samples, a quadratic cost function with respect to each row of the unmixing matrix, together with a linear constraint in relation to the involved variables, is proposed. Upon which, an algorithm is presented to estimate the unmixing matrix by solving a classical convex optimization problem. Unlike the traditional blind source separation (BSS) methods, the CG-based method does not require the independence assumption, nor the uncorrelation assumption. Compared with the BSS methods that are specifically designed to distinguish between nonnegative sources, the proposed method requires a weaker sparsity condition. Provided simulation results illustrate the performance of our method.
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This paper considers a framework where data from correlated sources are transmitted with the help of network coding in ad hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes in order to improve the data delivery performance. In such settings, we focus on the problem of reconstructing the sources at decoder when perfect decoding is not possible due to losses or bandwidth variations. We show that the source data similarity can be used at decoder to permit decoding based on a novel and simple approximate decoding scheme. We analyze the influence of the network coding parameters and in particular the size of finite coding fields on the decoding performance. We further determine the optimal field size that maximizes the expected decoding performance as a trade-off between information loss incurred by limiting the resolution of the source data and the error probability in the reconstructed data. Moreover, we show that the performance of the approximate decoding improves when the accuracy of the source model increases even with simple approximate decoding techniques. We provide illustrative examples showing how the proposed algorithm can be deployed in sensor networks and distributed imaging applications.
Resumo:
In this paper we address the problem of transmission of correlated sources over a fast fading multiple access channel (MAC) with partial channel state information available at both the encoders and the decoder. We provide sufficient conditions for transmission with given distortions. Next these conditions are specialized to a Gaussian MAC (GMAC). We provide the optimal power allocation strategy and compare the strategy with various levels of channel state information.
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In this paper, we consider a distributed function computation setting, where there are m distributed but correlated sources X1,...,Xm and a receiver interested in computing an s-dimensional subspace generated by [X1,...,Xm]Γ for some (m × s) matrix Γ of rank s. We construct a scheme based on nested linear codes and characterize the achievable rates obtained using the scheme. The proposed nested-linear-code approach performs at least as well as the Slepian-Wolf scheme in terms of sum-rate performance for all subspaces and source distributions. In addition, for a large class of distributions and subspaces, the scheme improves upon the Slepian-Wolf approach. The nested-linear-code scheme may be viewed as uniting under a common framework, both the Korner-Marton approach of using a common linear encoder as well as the Slepian-Wolf approach of employing different encoders at each source. Along the way, we prove an interesting and fundamental structural result on the nature of subspaces of an m-dimensional vector space V with respect to a normalized measure of entropy. Here, each element in V corresponds to a distinct linear combination of a set {Xi}im=1 of m random variables whose joint probability distribution function is given.
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Espécies de Aeromonas encontram-se distribuídas por diferentes habitats, estando especialmente relacionadas com ambientes aquáticos. O seu papel em complicações na saúde humana e animal é reconhecido. De facto, não só pelo seu potencial de virulência, mas também pelos determinantes genéticos de resistência a antibióticos que possam conter, estes organismos constituem uma preocupação na medicina humana e veterinária. Assim, é essencial o estudo da diversidade de espécies de Aeromonas bem como explorar as suas características fenotípicas e genéticas que podem conduzir a impactos negativos. A água constitui um importante veículo de transmissão de microrganismos e espécies de Aeromonas estão amplamente distribuídas em águas tratadas e não tratadas. Em Portugal é ainda comum o consumo de águas não tratadas cuja qualidade, na maioria das vezes, não é sujeita a monitorização, como acontece por exemplo, em explorações agrícolas de gestão familiar. Neste estudo, investigou-se a presença de Aeromonas em águas não tratadas para consumo. Estabeleceu-se também uma linha horizontal de colheitas de diferentes amostras de origem agrícola com o intuito de avaliar a possibilidade de a água ser uma das vias de contaminação de culturas agrícolas e animais por espécies de Aeromonas. Obtiveram-se 483 isolados que foram discriminados por RAPD-PCR. 169 estirpes distintas foram identificadas ao nível da espécie por análise filogenética baseada no gene gyrB. Verificou-se uma frequente ocorrência bem como uma diversidade considerável de espécies de Aeromonas. Em alguns casos, as relações genotípicas entre isolados de diferentes amostras eram muito próximas. Adicionalmente, a maioria das amostras continha diferentes espécies e estirpes distintas da mesma espécie. A. media e A. hydrophila foram as espécies mais ocorrentes. Um grupo de isolados apresentou variantes moleculares de gyrB diferente das conhecidas até agora, o que indica que poderão constituir espécies não descritas. O perfil de susceptibilidade da colecção de Aeromonas a diferentes antibióticos foi estabelecido, constituindo um perfil típico do género, com algumas excepções. Estirpes multirresistentes foram encontradas. A presença de genes tet e bla foi investigada por estudos de PCR, hibridação e, em alguns casos, de sequenciação. Como era esperado, cphA/imiS foi o mais detectado. A detecção de integrões fez-se por PCR e hibridação e a sua caracterização foi feita por sequenciação de DNA; a sua ocorrência foi reduzida. A maioria das estirpes sintetizou enzimas extracelulares com actividade lipolítica e proteolítica que potencialmente contribuem para virulência. A análise por PCR e hibridação permitiram a detecção de vários determinantes genéticos que codificam moléculas possivelmente envolvidas em processos patogénicos. Diversas espécies de Aeromonas apresentando características relacionadas com resistência a antibióticos e potencialmente de virulência estão frequentemente presentes em produtos para consumo humano e animal em Portugal. ABSTRACT: Aeromonas spp. are present in a wide range of ecological niches, being mainly related to aquatic environments. Their role in human and animal health complications is recognised. In fact, not only for their putative virulence but also for the antibiotic resistance genetic determinants Aeromonas may harbour, these organisms constitute an issue of concern in human and veterinary medicine. Thus, it is essential to get knowledge on Aeromonas sp. diversity and on their genotypic and phenotypic characteristics that may lead to negative impacts. Water constitutes a good contamination route for microorganisms and Aeromonas are widespread in untreated and treated waters from different sources. In Portugal there is still an extensive use of untreated water which is not regularly monitored for quality. This is often the case in family smallholding farms. In this study untreated drinking and mineral waters were assessed for their content in Aeromonas spp. Furthermore, a sampling scheme was designed to investigate the occurrence and diversity of Aeromonas sp. in different agricultural correlated sources and to assess the possibility of water being the transmission vehicle between those sources. 483 isolates were obtained and discriminated by RAPD-PCR. Identification at the species level for 169 distinct strains was done by gyrB based phylogenetic analysis. Results demonstrated the frequent occurrence and considerable diversity of Aeromonas spp. In some cases, genotypic close relations were found between isolates from different sources. Also, most samples contained different species and distinct strains of the same species. A. media and A. hydrophila were the most occurring. A group of isolates displayed gyrB gene sequences distinct from the previously known, indicating that they may constitute representatives of non-described species. The antibiotic susceptibility profile of the aeromonads collection was established and constituted a typical profile of the genus, although few exceptions. Multiresistance patterns were found. The presence of tet and bla genes was investigated by PCR, hybridisation and, in some cases, sequencing analysis. As expected, cphA/imiS was the most detected. Integrons were screened by PCR and hybridisation and characterised by DNA sequencing; low occurrence was recorded. The bulk of strains was able to produce extracellular enzymes with lipolytic and proteolytic activities, which may contribute to virulence. PCR and hybridisation surveys allowed the detection of distinct genetic determinants coding for molecules putatively involved in pathogenic processes. Diverse Aeromonas sp. presenting distinct antibiotic resistance features and putative virulence traits are frequently present in many sources for human and animal consumption in Portugal.
Resumo:
MEG beamformer algorithms work by making the assumption that correlated and spatially distinct local field potentials do not develop in the human brain. Despite this assumption, images produced by such algorithms concur with those from other non-invasive and invasive estimates of brain function. In this paper we set out to develop a method that could be applied to raw MEG data to explicitly test his assumption. We show that a promax rotation of MEG channel data can be used as an approximate estimator of the number of spatially distinct correlated sources in any frequency band.
Resumo:
The auditory evoked N1m-P2m response complex presents a challenging case for MEG source-modelling, because symmetrical, phase-locked activity occurs in the hemispheres both contralateral and ipsilateral to stimulation. Beamformer methods, in particular, can be susceptible to localisation bias and spurious sources under these conditions. This study explored the accuracy and efficiency of event-related beamformer source models for auditory MEG data under typical experimental conditions: monaural and diotic stimulation; and whole-head beamformer analysis compared to a half-head analysis using only sensors from the hemisphere contralateral to stimulation. Event-related beamformer localisations were also compared with more traditional single-dipole models. At the group level, the event-related beamformer performed equally well as the single-dipole models in terms of accuracy for both the N1m and the P2m, and in terms of efficiency (number of successful source models) for the N1m. The results yielded by the half-head analysis did not differ significantly from those produced by the traditional whole-head analysis. Any localisation bias caused by the presence of correlated sources is minimal in the context of the inter-individual variability in source localisations. In conclusion, event-related beamformers provide a useful alternative to equivalent-current dipole models in localisation of auditory evoked responses.