Search results for "algorithm."

showing 10 items of 4617 documents

Assessment of nonnegative matrix factorization algorithms for electroencephalography spectral analysis.

2020

AbstractBackgroundNonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed. However, the performance of their use in EEG data analysis has not been fully compared. Here, we provide a comparison of four NMF algorithms in terms of accuracy of estimation, stability (repeatability of the results) and time complexity of algorithms with simulated data. In the practical application of NMF algorithms, stability plays an important role, which was an emphasis in the comparison. A Hierarchical clustering algorithm was implemented to evaluate the stability of NM…

lcsh:Medical technologyComputer scienceBiomedical EngineeringStability (learning theory)ElectroencephalographySignal-To-Noise RatioClusteringNon-negative matrix factorizationBiomaterialsNonnegative matrix factorization03 medical and health sciencesklusterit0302 clinical medicineEeg dataalgoritmitmedicineHumansRadiology Nuclear Medicine and imagingSpectral analysisstabiilius (muuttumattomuus)EEGCluster analysisTime complexity030304 developmental biology0303 health sciencesRadiological and Ultrasound Technologymedicine.diagnostic_testResearchnonnegative matrix factorizationElectroencephalographySignal Processing Computer-AssistedGeneral MedicinestabilityModels TheoreticalHierarchical clusteringlcsh:R855-855.5AlgorithmStability030217 neurology & neurosurgeryAlgorithmsclusteringspektrianalyysiBiomedical engineering online
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All-Possible-Couplings Approach to Measuring Probabilistic Context.

2013

From behavioral sciences to biology to quantum mechanics, one encounters situations where (i) a system outputs several random variables in response to several inputs, (ii) for each of these responses only some of the inputs may "directly" influence them, but (iii) other inputs provide a "context" for this response by influencing its probabilistic relations to other responses. These contextual influences are very different, say, in classical kinetic theory and in the entanglement paradigm of quantum mechanics, which are traditionally interpreted as representing different forms of physical determinism. One can mathematically construct systems with other types of contextuality, whether or not …

lcsh:MedicineQuantum entanglementSocial and Behavioral Sciences01 natural sciencesQuantitative Biology - Quantitative MethodsJoint probability distributionPsychologyStatistical physicslcsh:ScienceQuantumQuantitative Methods (q-bio.QM)60B99 (Primary) 81Q99 91E45 (Secondary)PhysicsQuantum PhysicsMultidisciplinaryApplied MathematicsPhysics05 social sciencesComplex SystemsMental HealthMedicineMathematics - ProbabilityAlgorithmsResearch ArticleFOS: Physical sciencesContext (language use)Physical determinism050105 experimental psychologyProbability theory0103 physical sciencesFOS: Mathematics0501 psychology and cognitive sciences010306 general physicsQuantum MechanicsProbabilityta113BehaviorModels Statisticallcsh:RProbability (math.PR)Probabilistic logicRandom VariablesProbability TheoryKochen–Specker theoremFOS: Biological sciencesQuantum Theorylcsh:QQuantum EntanglementQuantum Physics (quant-ph)Mathematics
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Approaching electrical tomography

2009

A general approach to electrical tomography is here described, based on the distribution of the experimental data to the set of voxels in which the subsoil has been divided. This approach utilizes the sensitivity coefficients as factors of the convolution procedure to execute the back projection of the data, to obtain the 3D pictures of the subsoil. A subsequent probabilistic filtering technique is described to improve the pictures in view of sharp boundary models. Some models are finally presented, mostly regarding cubic buried anomalies as well as pipe-shaped and L-shaped anomalies.

lcsh:QC801-809Probabilistic logicBoundary (topology)Geometrylcsh:QC851-999computer.software_genreConvolutionSet (abstract data type)Electrical tomographylcsh:Geophysics. Cosmic physicsGeophysicsDistribution (mathematics)Voxelelectrone gridback projectionlcsh:Meteorology. ClimatologySensitivity (control systems)TomographycomputerAlgorithmMathematicsAnnals of Geophysics
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A Combined Multi-Cohort Approach Reveals Novel and Known Genome-Wide Selection Signatures for Wool Traits in Merino and Merino-Derived Sheep Breeds.

2019

Merino sheep represents a valuable genetic resource worldwide. In this study, we investigated selection signatures in Merino (and Merino-derived) sheep breeds using genome-wide SNP data and two different approaches: a classical F-ST-outlier method and an approach based on the analysis of local ancestry in admixed populations. In order to capture the most reliable signals, we adopted a combined, multi-cohort approach. In particular, scenarios involving four Merino breeds (Spanish Merino, Australian Merino, Chinese Merino, and Sopravissana) were tested via the local ancestry approach, while nine pair-wise breed comparisons contrasting the above breeds, as well as the Gentile di Puglia breed, …

lcsh:QH426-470Runs of HomozygosityBiologyRuns of homozygosityGenomeFst-outlierMerino sheep breedsSettore AGR/17 - Zootecnica Generale E Miglioramento GeneticoGeneticsGenetics (clinical)Selection (genetic algorithm)Original ResearchGeographic areaWoollocal ancestry in admixed populationsLocal ancestry in admixed populationPhenotypeSignal onBreedGenome-wide selection signaturelcsh:GeneticsWoolEvolutionary biologyMerino sheep breedMolecular Medicinegenome-wide selection signaturesFrontiers in genetics
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Special Issue on Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition

2018

This special issue of Algorithms is devoted to the study of Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition. The special issue considered both theoretical contributions able to advance the state-of-the-art in this field and practical applications that describe novel approaches for solving real-world problems.

lcsh:T55.4-60.8Computer science020209 energyComputational intelligence02 engineering and technologylcsh:QA75.5-76.95Field (computer science)Theoretical Computer Science0202 electrical engineering electronic engineering information engineeringlcsh:Industrial engineering. Management engineeringNature inspireddata analyticsNumerical Analysisbusiness.industrypattern recognitionComputational mathematicsPattern recognitionnature-inspired algorithmsComputational MathematicsComputational Theory and MathematicsAnalyticsPattern recognition (psychology)Computational IntelligenceData analysislcsh:Electronic computers. Computer scienceArtificial intelligencebusinessReal world dataAlgorithmAlgorithms
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System identification via optimised wavelet-based neural networks

2003

Nonlinear system identification by means of wavelet-based neural networks (WBNNs) is presented. An iterative method is proposed, based on a way of combining genetic algorithms (GAs) and least-square techniques with the aim of avoiding redundancy in the representation of the function. GAs are used for optimal selection of the structure of the WBNN and the parameters of the transfer function of its neurones. Least-square techniques are used to update the weights of the net. The basic criterion of the method is the addition of a new neurone, at a generic step, to the already constructed WBNN so that no modification to the parameters of its neurones is required. Simulation experiments and compa…

least squares approximations nonlinear dynamical systems identification neural nets iterative methods genetic algorithmsQuantitative Biology::Neurons and CognitionArtificial neural networkNonlinear system identificationIterative methodComputer scienceSystem identificationTransfer functionWaveletSettore ING-INF/04 - AutomaticaControl and Systems EngineeringControl theoryRedundancy (engineering)Electrical and Electronic EngineeringRepresentation (mathematics)InstrumentationAlgorithmIEE Proceedings - Control Theory and Applications
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Multilayer perceptron training with multiobjective memetic optimization

2016

Machine learning tasks usually come with several mutually conflicting objectives. One example is the simplicity of the learning device contrasted with the accuracy of its performance after learning. Another common example is the trade-off that must often be made between the rate of false positive and false negative predictions in diagnostic applications. For computer programs that learn from data, these objectives are formulated as mathematical functions, each of which describes one facet of the desired learning outcome. Even functions that intend to optimize the same facet may behave in a subtly different and mutually conflicting way, depending on the task and the dataset being examined. Mul…

machine learningkoneoppiminenclassification algorithmsmemeettiset algoritmitalgoritmitmultiobjective optimizationmultilayer perceptronmemetic algorithmsneuroverkotmatemaattinen optimointineural networksluokitus
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Compensated transfer entropy as a tool for reliably estimating information transfer in physiological time series

2013

We present a framework for the estimation of transfer entropy (TE) under the conditions typical of physiological system analysis, featuring short multivariate time series and the presence of instantaneous causality (IC). The framework is based on recognizing that TE can be interpreted as the difference between two conditional entropy (CE) terms, and builds on an efficient CE estimator that compensates for the bias occurring for high dimensional conditioning vectors and follows a sequential embedding procedure whereby the conditioning vectors are formed progressively according to a criterion for CE minimization. The issue of IC is faced accounting for zero-lag interactions according to two a…

magnetoencephalographyInformation transferinstantaneous causalityGeneral Physics and Astronomylcsh:AstrophysicsMachine learningcomputer.software_genreconditional entropyPhysics and Astronomy (all)lcsh:QB460-466False positive paradoxSensitivity (control systems)lcsh:ScienceMathematicsConditional entropytime delay embeddingSeries (mathematics)business.industryEstimatorlcsh:QC1-999Cardiovascular variability; Conditional entropy; Instantaneous causality; Magnetoencephalography; Time delay embedding; Physics and Astronomy (all)Settore ING-INF/06 - Bioingegneria Elettronica E InformaticaTransfer entropylcsh:QArtificial intelligenceMinificationcardiovascular variabilitycardiovascular variability; conditional entropy; instantaneous causality; magnetoencephalography; time delay embeddingbusinesscomputerAlgorithmlcsh:Physics
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Abonder une base EndNote avec un formulaire web et un courriel

2011

National audience; Cet article présente une façon originale d’abonder une base EndNote en limitant le nombre d’erreurs et les doubles saisies. Cette procédure permet d’utiliser un canal unique et d’avoir les informations utiles à leur exploitation. La saisie s’effectue via un formulaire disponible sur l’intranet de l’unité, les données sont intégrées dans un fichier XML et envoyées par courriel à la documentaliste avec éventuellement une pièce attachée pour intégration directe à la base avec la fonction import d’EndNote.

mail[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS][INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]XMLcourrielEndnotebibliographie
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Best Practices in Constant pH MD Simulations: Accuracy and Sampling

2022

Various approaches have been proposed to include the effect of pH in molecular dynamics (MD) simulations. Among these, the λ-dynamics approach proposed by Brooks and co-workers [Kong, X.; Brooks III, C. L. J. Chem. Phys.1996, 105, 2414−2423] can be performed with little computational overhead and hfor each typeence be used to routinely perform MD simulations at microsecond time scales, as shown in the accompanying paper [Aho, N. et al. J. Chem. Theory Comput.2022, DOI: 10.1021/acs.jctc.2c00516]. At such time scales, however, the accuracy of the molecular mechanics force field and the parametrization becomes critical. Here, we address these issues and provide the community with guidelines on…

mallintaminenEntropyProteinsmolekyylitHydrogen-Ion ConcentrationMolecular Dynamics Simulationmonomerspeptides and proteinsreaktiomekanismitmolecular mechanicsComputer Science Applicationsreaction mechanismspeptiditHumanscomputer simulationssimulointimolekyylidynamiikkaproteiinitPhysical and Theoretical ChemistryAlgorithmsJournal of Chemical Theory and Computation
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