972 resultados para pseudo-random number generator


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Wireless “MIMO” systems, employing multiple transmit and receive antennas, promise a significant increase of channel capacity, while orthogonal frequency-division multiplexing (OFDM) is attracting a good deal of attention due to its robustness to multipath fading. Thus, the combination of both techniques is an attractive proposition for radio transmission. The goal of this paper is the description and analysis of a new and novel pilot-aided estimator of multipath block-fading channels. Typical models leading to estimation algorithms assume the number of multipath components and delays to be constant (and often known), while their amplitudes are allowed to vary with time. Our estimator is focused instead on the more realistic assumption that the number of channel taps is also unknown and varies with time following a known probabilistic model. The estimation problem arising from these assumptions is solved using Random-Set Theory (RST), whereby one regards the multipath-channel response as a single set-valued random entity.Within this framework, Bayesian recursive equations determine the evolution with time of the channel estimator. Due to the lack of a closed form for the solution of Bayesian equations, a (Rao–Blackwellized) particle filter (RBPF) implementation ofthe channel estimator is advocated. Since the resulting estimator exhibits a complexity which grows exponentially with the number of multipath components, a simplified version is also introduced. Simulation results describing the performance of our channel estimator demonstrate its effectiveness.

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In this paper, we introduce a pilot-aided multipath channel estimator for Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) systems. Typical estimation algorithms assume the number of multipath components and delays to be known and constant, while theiramplitudes may vary in time. In this work, we focus on the more realistic assumption that also the number of channel taps is unknown and time-varying. The estimation problem arising from this assumption is solved using Random Set Theory (RST), which is a probability theory of finite sets. Due to the lack of a closed form of the optimal filter, a Rao-Blackwellized Particle Filter (RBPF) implementation of the channel estimator is derived. Simulation results demonstrate the estimator effectiveness.

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Introduction: Responses to external stimuli are typically investigated by averaging peri-stimulus electroencephalography (EEG) epochs in order to derive event-related potentials (ERPs) across the electrode montage, under the assumption that signals that are related to the external stimulus are fixed in time across trials. We demonstrate the applicability of a single-trial model based on patterns of scalp topographies (De Lucia et al, 2007) that can be used for ERP analysis at the single-subject level. The model is able to classify new trials (or groups of trials) with minimal a priori hypotheses, using information derived from a training dataset. The features used for the classification (the topography of responses and their latency) can be neurophysiologically interpreted, because a difference in scalp topography indicates a different configuration of brain generators. An above chance classification accuracy on test datasets implicitly demonstrates the suitability of this model for EEG data. Methods: The data analyzed in this study were acquired from two separate visual evoked potential (VEP) experiments. The first entailed passive presentation of checkerboard stimuli to each of the four visual quadrants (hereafter, "Checkerboard Experiment") (Plomp et al, submitted). The second entailed active discrimination of novel versus repeated line drawings of common objects (hereafter, "Priming Experiment") (Murray et al, 2004). Four subjects per experiment were analyzed, using approx. 200 trials per experimental condition. These trials were randomly separated in training (90%) and testing (10%) datasets in 10 independent shuffles. In order to perform the ERP analysis we estimated the statistical distribution of voltage topographies by a Mixture of Gaussians (MofGs), which reduces our original dataset to a small number of representative voltage topographies. We then evaluated statistically the degree of presence of these template maps across trials and whether and when this was different across experimental conditions. Based on these differences, single-trials or sets of a few single-trials were classified as belonging to one or the other experimental condition. Classification performance was assessed using the Receiver Operating Characteristic (ROC) curve. Results: For the Checkerboard Experiment contrasts entailed left vs. right visual field presentations for upper and lower quadrants, separately. The average posterior probabilities, indicating the presence of the computed template maps in time and across trials revealed significant differences starting at ~60-70 ms post-stimulus. The average ROC curve area across all four subjects was 0.80 and 0.85 for upper and lower quadrants, respectively and was in all cases significantly higher than chance (unpaired t-test, p<0.0001). In the Priming Experiment, we contrasted initial versus repeated presentations of visual object stimuli. Their posterior probabilities revealed significant differences, which started at 250ms post-stimulus onset. The classification accuracy rates with single-trial test data were at chance level. We therefore considered sub-averages based on five single trials. We found that for three out of four subjects' classification rates were significantly above chance level (unpaired t-test, p<0.0001). Conclusions: The main advantage of the present approach is that it is based on topographic features that are readily interpretable along neurophysiologic lines. As these maps were previously normalized by the overall strength of the field potential on the scalp, a change in their presence across trials and between conditions forcibly reflects a change in the underlying generator configurations. The temporal periods of statistical difference between conditions were estimated for each training dataset for ten shuffles of the data. Across the ten shuffles and in both experiments, we observed a high level of consistency in the temporal periods over which the two conditions differed. With this method we are able to analyze ERPs at the single-subject level providing a novel tool to compare normal electrophysiological responses versus single cases that cannot be considered part of any cohort of subjects. This aspect promises to have a strong impact on both basic and clinical research.

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We examine a multiple-access communication system in which multiuser detection is performed without knowledge of the number of active interferers. Using a statistical-physics approach, we compute the single-user channel capacity and spectral efficiency in the large-system limit.

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One evolutionary explanation for the success of sexual reproduction assumes that sex is an advantage in the coevolutionary arms race between pathogens and hosts. Accordingly, an important criterion in mate choice and maternal selection thereafter could be the allelic specificity at polymorphic loci involved in parasite-host interactions, e.g. the MHC (major histocompatibility complex). The MHC has been found to influence mate choice and selective abortions in mice and humans. However, it could also influence the fertilization process itself, i.e. (i) the oocyte's choice for the fertilizing sperm, and (ii) the outcome of the second meiotic division after the sperm has entered the egg. We tested both hypotheses in an in vitro fertilization experiment with two inbred mouse strains congenic for their MHC. The genotypes of the resulting blastocysts were determined by polymerase chain reaction. We found nonrandom MHC combinations in the blastocysts which may result from both possible choice mechanisms. The outcome changed significantly over time, indicating that a choice for MHC combinations during fertilization may be influenced by one or several external factors.

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The breeding system of social organisms affects many important aspects of social life. Some species vary greatly in the number of breeders per group, but the mechanisms and selective pressures contributing to the maintenance of this polymorphism in social structure remain poorly understood. Here, we take advantage of a genetic dataset that spans 15 years to investigate the dynamics of colony queen number within a socially polymorphic ant species. Our study population of Formica selysi has single- and multiple-queen colonies. We found that the social structure of this species is somewhat flexible: on average, each year 3.2% of the single-queen colonies became polygynous, and conversely 1.4% of the multiple-queen colonies became monogynous. The annualized queen replacement rates were 10.3% and 11.9% for single- and multiple-queen colonies, respectively. New queens were often but not always related to previous colony members. At the population level, the social polymorphism appeared stable. There was no genetic differentiation between single- and multiple-queen colonies at eight microsatellite loci, suggesting ongoing gene flow between social forms. Overall, the regular and bidirectional changes in queen number indicate that social structure is a labile trait in F. selysi, with neither form being favored within a time-frame of 15 years.

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This paper explores the existence of negative peer-group pressures derived from the concentration of foreigners in French lower secondary schools. Using different dependent variables (number of years spent in lower secondary education, grades in 4th ‘and 3rd year and track election in upper secondary schooling) the analyses indicate that the much disputed existence of significant and negative effects of the concentration of foreign students in schools depends on the method used for the estimation. If we assume that the concentration of foreigners is a random and exogenous process, then the multivariate analyses confirm negative interactions. If, on the contrary, we question the assumption that this contextual information is not end the result of prior sorting mechanisms of individuals across social spaces, the concentration of foreigners has no statistical impact on attainment.

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Epidemiological processes leave a fingerprint in the pattern of genetic structure of virus populations. Here, we provide a new method to infer epidemiological parameters directly from viral sequence data. The method is based on phylogenetic analysis using a birth-death model (BDM) rather than the commonly used coalescent as the model for the epidemiological transmission of the pathogen. Using the BDM has the advantage that transmission and death rates are estimated independently and therefore enables for the first time the estimation of the basic reproductive number of the pathogen using only sequence data, without further assumptions like the average duration of infection. We apply the method to genetic data of the HIV-1 epidemic in Switzerland.

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In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

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Excecutive order signed by Governor Thomas Vilsck. Ensures Iowa's kids have a quality early childhood experience by giving child care workers the opportunity to organize. Directs the Department of Human Services to meet with authorized representatives of unregistered Child Care providers (and others not covered by Executive Order 45 )in the State of Iowa.

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Excecutive order signed by Governor Thomas Vilsck. Grants voting rights to disqualified electors who have discharged their sentence, probation or parole.

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Excecutive order signed by Governor Thomas Vilsck. Directs the Department of Human Services to meet with organizations and associations in order to improve delivery and quality of home and community-based care services for Iowa’s elderly and disabled.

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Excecutive order signed by Governor Thomas Vilsck. Directs the Department of Human Services to comply with all directives from the federal government arising from Hurricane Katrina insofar as those directives concern public welfare programs administered by DHS, declares that any evacuee shall be deemed a resident of the State of Iowa for purposes of obtaining eligibility for the food stamp, family investment and Medicaid programs, and DHS should process applications in an expedited and flexible manner.

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Excecutive order signed by Governor Thomas Vilsck. Ensures Iowa's kids have a quality early childhood experience by giving child care workers the opportunity to organize. Directs the Department of Human Services to meet with authorized representatives of Registered Child Care providers in the State of Iowa.