992 resultados para Maximum distance separable (MDS) convolutional codes


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A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.

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This article reports on a project at the Universitat Oberta de Catalunya (UOC: The Open University of Catalonia, Barcelona) to develop an innovative package of hypermedia-based learning materials for a new course entitled 'Current Issues in Marketing'. The UOC is a distance university entirely based on a virtual campus. The learning materials project was undertaken in order to benefit from the advantages which new communication technologies offer to the teaching of marketing in distance education. The article reviews the main issues involved in incorporating new technologies in learning materials, the development of the learning materials, and their functioning within the hypermedia based virtual campus of the UOC. An empirical study is then carried out in order to evaluate the attitudes of students to the project. Finally, suggestions for improving similar projects in the future are put forward.

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A new coding technique to be used in steganography is evaluated. The performanceof this new technique is computed and comparisons with the well-known theoreticalupper bound, Hamming upper bound and basic LSB are established.

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The objective of this work was to isolate strains of lactic acid bacteria with probiotic potential from the digestive tract of marine shrimp (Litopenaeus vannamei), and to carry out in vitro selection based on multiple characters. The ideotype (ideal proposed strain) was defined by the highest averages for the traits maximum growth velocity, final count of viable cells, and inhibition halo against nine freshwater and marine pathogens, and by the lowest averages for the traits duplication time and resistance of strains to NaCl (1.5 and 3%), pH (6, 8, and 9), and biliary salts (5%). Mahalanobis distance (D²) was estimated among the evaluated strains, and the best ones were those with the shortest distances to the ideotype. Ten bacterial strains were isolated and biochemically identified as Lactobacillus plantarum (3), L. brevis (3), Weissella confusa (2), Lactococcus lactis (1), and L. delbrueckii (1). Lactobacillus plantarum strains showed a wide spectrum of action and the largest inhibition halos against pathogens, both Gram-positive and negative, high growth rate, and tolerance to all evaluated parameters. In relation to ideotype, L. plantarum showed the lowest Mahalanobis (D²) distance, followed by the strains of W. confusa, L. brevis, L. lactis, and L. delbrueckii. Among the analyzed bacterial strains, those of Lactobacillus plantarum have the greatest potential for use as a probiotic for marine shrimp.

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This paper analyzes the asymptotic performance of maximum likelihood (ML) channel estimation algorithms in wideband code division multiple access (WCDMA) scenarios. We concentrate on systems with periodic spreading sequences (period larger than or equal to the symbol span) where the transmitted signal contains a code division multiplexed pilot for channel estimation purposes. First, the asymptotic covariances of the training-only, semi-blind conditional maximum likelihood (CML) and semi-blind Gaussian maximum likelihood (GML) channelestimators are derived. Then, these formulas are further simplified assuming randomized spreading and training sequences under the approximation of high spreading factors and high number of codes. The results provide a useful tool to describe the performance of the channel estimators as a function of basicsystem parameters such as number of codes, spreading factors, or traffic to training power ratio.

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This paper is concerned with the derivation of new estimators and performance bounds for the problem of timing estimation of (linearly) digitally modulated signals. The conditional maximum likelihood (CML) method is adopted, in contrast to the classical low-SNR unconditional ML (UML) formulationthat is systematically applied in the literature for the derivationof non-data-aided (NDA) timing-error-detectors (TEDs). A new CML TED is derived and proved to be self-noise free, in contrast to the conventional low-SNR-UML TED. In addition, the paper provides a derivation of the conditional Cramér–Rao Bound (CRB ), which is higher (less optimistic) than the modified CRB (MCRB)[which is only reached by decision-directed (DD) methods]. It is shown that the CRB is a lower bound on the asymptotic statisticalaccuracy of the set of consistent estimators that are quadratic with respect to the received signal. Although the obtained boundis not general, it applies to most NDA synchronizers proposed in the literature. A closed-form expression of the conditional CRBis obtained, and numerical results confirm that the CML TED attains the new bound for moderate to high Eg/No.

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The continuous wavelet transform is obtained as a maximumentropy solution of the corresponding inverse problem. It is well knownthat although a signal can be reconstructed from its wavelet transform,the expansion is not unique due to the redundancy of continuous wavelets.Hence, the inverse problem has no unique solution. If we want to recognizeone solution as "optimal", then an appropriate decision criterion hasto be adopted. We show here that the continuous wavelet transform is an"optimal" solution in a maximum entropy sense.

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This paper provides a systematic approach to theproblem of nondata aided symbol-timing estimation for linearmodulations. The study is performed under the unconditionalmaximum likelihood framework where the carrier-frequencyerror is included as a nuisance parameter in the mathematicalderivation. The second-order moments of the received signal arefound to be the sufficient statistics for the problem at hand and theyallow the provision of a robust performance in the presence of acarrier-frequency error uncertainty. We particularly focus on theexploitation of the cyclostationary property of linear modulations.This enables us to derive simple and closed-form symbol-timingestimators which are found to be based on the well-known squaretiming recovery method by Oerder and Meyr. Finally, we generalizethe OM method to the case of linear modulations withoffset formats. In this case, the square-law nonlinearity is foundto provide not only the symbol-timing but also the carrier-phaseerror.

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In this letter, we obtain the Maximum LikelihoodEstimator of position in the framework of Global NavigationSatellite Systems. This theoretical result is the basis of a completelydifferent approach to the positioning problem, in contrastto the conventional two-steps position estimation, consistingof estimating the synchronization parameters of the in-viewsatellites and then performing a position estimation with thatinformation. To the authors’ knowledge, this is a novel approachwhich copes with signal fading and it mitigates multipath andjamming interferences. Besides, the concept of Position–basedSynchronization is introduced, which states that synchronizationparameters can be recovered from a user position estimation. Weprovide computer simulation results showing the robustness ofthe proposed approach in fading multipath channels. The RootMean Square Error performance of the proposed algorithm iscompared to those achieved with state-of-the-art synchronizationtechniques. A Sequential Monte–Carlo based method is used todeal with the multivariate optimization problem resulting fromthe ML solution in an iterative way.

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A detailed mathematical analysis on the q = 1/2 non-extensive maximum entropydistribution of Tsallis' is undertaken. The analysis is based upon the splitting of such adistribution into two orthogonal components. One of the components corresponds to theminimum norm solution of the problem posed by the fulfillment of the a priori conditionson the given expectation values. The remaining component takes care of the normalizationconstraint and is the projection of a constant onto the Null space of the "expectation-values-transformation"

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A regularization method based on the non-extensive maximum entropy principle is devised. Special emphasis is given to the q=1/2 case. We show that, when the residual principle is considered as constraint, the q=1/2 generalized distribution of Tsallis yields a regularized solution for bad-conditioned problems. The so devised regularized distribution is endowed with a component which corresponds to the well known regularized solution of Tikhonov (1977).

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A maximum entropy statistical treatment of an inverse problem concerning frame theory is presented. The problem arises from the fact that a frame is an overcomplete set of vectors that defines a mapping with no unique inverse. Although any vector in the concomitant space can be expressed as a linear combination of frame elements, the coefficients of the expansion are not unique. Frame theory guarantees the existence of a set of coefficients which is “optimal” in a minimum norm sense. We show here that these coefficients are also “optimal” from a maximum entropy viewpoint.

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Abstract: The objective of this work was to identify polymorphic simple sequence repeat (SSR) markers for varietal identification of cotton and evaluation of the genetic distance among the varieties. Initially, 92 SSR markers were genotyped in 20 Brazilian cotton cultivars. Of this total, 38 loci were polymorphic, two of which were amplified by one primer pair; the mean number of alleles per locus was 2.2. The values of polymorphic information content (PIC) and discrimination power (DP) were, on average, 0.374 and 0.433, respectively. The mean genetic distance was 0.397 (minimum of 0.092 and maximum of 0.641). A panel of 96 varieties originating from different regions of the world was assessed by 21 polymorphic loci derived from 17 selected primer pairs. Among these varieties, the mean genetic distance was 0.387 (minimum of 0 and maximum of 0.786). The dendrograms generated by the unweighted pair group method with arithmetic average (UPGMA) did not reflect the regions of Brazil (20 genotypes) or around the world (96 genotypes), where the varieties or lines were selected. Bootstrap resampling shows that genotype identification is viable with 19 loci. The polymorphic markers evaluated are useful to perform varietal identification in a large panel of cotton varieties and may be applied in studies of the species diversity.

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Diplomityön tavoitteena on paineistimen yksityiskohtainen mallintaminen APROS- ja TRACE- termohydrauliikkaohjelmistoja käyttäen. Rakennetut paineistinmallit testattiin vertaamalla laskentatuloksia paineistimen täyttymistä, tyhjentymistä ja ruiskutusta käsittelevistä erilliskokeista saatuun mittausdataan. Tutkimuksen päätavoitteena on APROSin paineistinmallin validoiminen käyttäen vertailuaineistona PACTEL ATWS-koesarjan sopivia paineistinkokeita sekä MIT Pressurizer- ja Neptunus- erilliskokeita. Lisäksi rakennettiin malli Loviisan ydinvoimalaitoksen paineistimesta, jota käytettiin turbiinitrippitransientin simulointiin tarkoituksena selvittää mahdolliset voimalaitoksen ja koelaitteistojen mittakaavaerosta johtuvat vaikutukset APROSin paineistinlaskentaan. Kokeiden simuloinnissa testattiin erilaisia noodituksia ja mallinnusvaihtoehtoja, kuten entalpian ensimmäisen ja toisen kertaluvun diskretisointia, ja APROSin sekä TRACEn antamia tuloksia vertailtiin kattavasti toisiinsa. APROSin paineistinmallin lämmönsiirtokorrelaatioissa havaittiin merkittävä puute ja laskentatuloksiin saatiin huomattava parannus ottamalla käyttöön uusi seinämälauhtumismalli. Työssä tehdyt TRACE-simulaatiot ovat osa United States Nuclear Regulatory Commissionin kansainvälistä CAMP-koodinkehitys-ja validointiohjelmaa.