885 resultados para Filtro de difusão linear
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O objetivo deste trabalho foi determinar o tamanho de amostra para a estimação do coeficiente de correlação linear de Pearson entre caracteres de três híbridos de milho. Para as análises, foram tomadas aleatoriamente 361, 373 e 416 plantas, respectivamente, de híbridos simples, triplo e duplo. Para cada planta, os seguintes caracteres foram mensurados: diâmetro maior e menor do colmo, altura da planta e altura, peso, comprimento e diâmetro da espiga, número de fileiras por espiga, peso e diâmetro de sabugo, massa de cem grãos, número de grãos por espiga, comprimento e produtividade de grãos. Para cada um dos 91 pares de caracteres e híbridos, foi determinado o tamanho de amostra a partir de "bootstrap", com reposição de 1.000 amostras, de cada tamanho de amostra simulado. Na estimação do coeficiente de correlação linear de Pearson com a mesma precisão, o tamanho de amostra (número de plantas) aumenta na direção de pares de caracteres com menor intensidade de relação linear, independentemente do tipo de híbrido. Para os 91 pares de caracteres estudados, 252 plantas são suficientes para a estimação do coeficiente de correlação linear de Pearson, no intervalo de confiança de "bootstrap" de 95%, igual a 0,30
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[Abstract]
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The objective of this work was to assess the degree of multicollinearity and to identify the variables involved in linear dependence relations in additive-dominant models. Data of birth weight (n=141,567), yearling weight (n=58,124), and scrotal circumference (n=20,371) of Montana Tropical composite cattle were used. Diagnosis of multicollinearity was based on the variance inflation factor (VIF) and on the evaluation of the condition indexes and eigenvalues from the correlation matrix among explanatory variables. The first model studied (RM) included the fixed effect of dam age class at calving and the covariates associated to the direct and maternal additive and non-additive effects. The second model (R) included all the effects of the RM model except the maternal additive effects. Multicollinearity was detected in both models for all traits considered, with VIF values of 1.03 - 70.20 for RM and 1.03 - 60.70 for R. Collinearity increased with the increase of variables in the model and the decrease in the number of observations, and it was classified as weak, with condition index values between 10.00 and 26.77. In general, the variables associated with additive and non-additive effects were involved in multicollinearity, partially due to the natural connection between these covariables as fractions of the biological types in breed composition.
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This paper suggests a method for obtaining efficiency bounds in models containing either only infinite-dimensional parameters or both finite- and infinite-dimensional parameters (semiparametric models). The method is based on a theory of random linear functionals applied to the gradient of the log-likelihood functional and is illustrated by computing the lower bound for Cox's regression model
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Peer-reviewed
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Abstract
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Correspondència referida a l'article de R. Giannetti, publicat ibid. vol.49 p.87-88
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In this paper, an advanced technique for the generation of deformation maps using synthetic aperture radar (SAR) data is presented. The algorithm estimates the linear and nonlinear components of the displacement, the error of the digital elevation model (DEM) used to cancel the topographic terms, and the atmospheric artifacts from a reduced set of low spatial resolution interferograms. The pixel candidates are selected from those presenting a good coherence level in the whole set of interferograms and the resulting nonuniform mesh tessellated with the Delauney triangulation to establish connections among them. The linear component of movement and DEM error are estimated adjusting a linear model to the data only on the connections. Later on, this information, once unwrapped to retrieve the absolute values, is used to calculate the nonlinear component of movement and atmospheric artifacts with alternate filtering techniques in both the temporal and spatial domains. The method presents high flexibility with respect to the required number of images and the baselines length. However, better results are obtained with large datasets of short baseline interferograms. The technique has been tested with European Remote Sensing SAR data from an area of Catalonia (Spain) and validated with on-field precise leveling measurements.
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Identifiability of the so-called ω-slice algorithm is proven for ARMA linear systems. Although proofs were developed in the past for the simpler cases of MA and AR models, they were not extendible to general exponential linear systems. The results presented in this paper demonstrate a unique feature of the ω-slice method, which is unbiasedness and consistency when order is overdetermined, regardless of the IIR or FIR nature of the underlying system, and numerical robustness.
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In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.
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This paper deals with the design of nonregenerativerelaying transceivers in cooperative systems where channel stateinformation (CSI) is available at the relay station. The conventionalnonregenerative approach is the amplify and forward(A&F) approach, where the signal received at the relay is simplyamplified and retransmitted. In this paper, we propose an alternativelinear transceiver design for nonregenerative relaying(including pure relaying and the cooperative transmission cases),making proper use of CSI at the relay station. Specifically, wedesign the optimum linear filtering performed on the data to beforwarded at the relay. As optimization criteria, we have consideredthe maximization of mutual information (that provides aninformation rate for which reliable communication is possible) fora given available transmission power at the relay station. Threedifferent levels of CSI can be considered at the relay station: onlyfirst hop channel information (between the source and relay);first hop channel and second hop channel (between relay anddestination) information, or a third situation where the relaymay have complete cooperative channel information includingall the links: first and second hop channels and also the directchannel between source and destination. Despite the latter beinga more unrealistic situation, since it requires the destination toinform the relay station about the direct channel, it is useful as anupper benchmark. In this paper, we consider the last two casesrelating to CSI.We compare the performance so obtained with theperformance for the conventional A&F approach, and also withthe performance of regenerative relays and direct noncooperativetransmission for two particular cases: narrowband multiple-inputmultiple-output transceivers and wideband single input singleoutput orthogonal frequency division multiplex transmissions.
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Microphthalmia with linear skin defects (MLS) syndrome is an X-linked male-lethal disorder also known as MIDAS (microphthalmia, dermal aplasia, and sclerocornea). Additional clinical features include neurological and cardiac abnormalities. MLS syndrome is genetically heterogeneous given that heterozygous mutations in HCCS or COX7B have been identified in MLS-affected females. Both genes encode proteins involved in the structure and function of complexes III and IV, which form the terminal segment of the mitochondrial respiratory chain (MRC). However, not all individuals with MLS syndrome carry a mutation in either HCCS or COX7B. The majority of MLS-affected females have severe skewing of X chromosome inactivation, suggesting that mutations in HCCS, COX7B, and other as-yet-unidentified X-linked gene(s) cause selective loss of cells in which the mutated X chromosome is active. By applying whole-exome sequencing and filtering for X-chromosomal variants, we identified a de novo nonsense mutation in NDUFB11 (Xp11.23) in one female individual and a heterozygous 1-bp deletion in a second individual, her asymptomatic mother, and an affected aborted fetus of the subject's mother. NDUFB11 encodes one of 30 poorly characterized supernumerary subunits of NADH:ubiquinone oxidoreductase, known as complex I (cI), the first and largest enzyme of the MRC. By shRNA-mediated NDUFB11 knockdown in HeLa cells, we demonstrate that NDUFB11 is essential for cI assembly and activity as well as cell growth and survival. These results demonstrate that X-linked genetic defects leading to the complete inactivation of complex I, III, or IV underlie MLS syndrome. Our data reveal an unexpected role of cI dysfunction in a developmental phenotype, further underscoring the existence of a group of mitochondrial diseases associated with neurocutaneous manifestations.