Search results for "Simulation"

showing 10 items of 5095 documents

Scalability of using Restricted Boltzmann Machines for Combinatorial Optimization

2014

Abstract Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Restricted Boltzmann Machines (RBMs) are generative neural networks with these desired properties. We integrate an RBM into an EDA and evaluate the performance of this system in solving combinatorial optimization problems with a single objective. We assess how the number of fitness evaluations and the CPU time scale with problem size and complexity. The results are compared to the Bayesian Optimization Algorithm (BOA), a state-of-the-art multivariate EDA, and the Dependency Tree Algorithm (DTA), which uses a simpler probability model requiring less computati…

FOS: Computer and information sciencesMathematical optimizationInformation Systems and ManagementOptimization problemGeneral Computer SciencePopulationComputer Science::Neural and Evolutionary Computation0211 other engineering and technologiesBoltzmann machine02 engineering and technologyManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringEvolutionary computation0202 electrical engineering electronic engineering information engineeringNeural and Evolutionary Computing (cs.NE)educationMathematicseducation.field_of_study021103 operations researchArtificial neural networkI.2.6I.2.8Computer Science - Neural and Evolutionary ComputingEstimation of distribution algorithmModeling and SimulationScalabilityCombinatorial optimization020201 artificial intelligence & image processingI.2.6; I.2.8Algorithm
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Fractional Spectral Moments for Digital Simulation of Multivariate Wind Velocity Fields

2012

In this paper, a method for the digital simulation of wind velocity fields by Fractional Spectral Moment function is proposed. It is shown that by constructing a digital filter whose coefficients are the fractional spectral moments, it is possible to simulate samples of the target process as superposition of Riesz fractional derivatives of a Gaussian white noise processes. The key of this simulation technique is the generalized Taylor expansion proposed by the authors. The method is extended to multivariate processes and practical issues on the implementation of the method are reported.

FOS: Computer and information sciencesMultivariate wind velocity fieldMultivariate statisticsStatistical Mechanics (cond-mat.stat-mech)Fractional spectral momentRenewable Energy Sustainability and the EnvironmentMechanical EngineeringMathematical analysisFOS: Physical sciencesGeneralized Taylor formWhite noiseFunction (mathematics)Digital simulation of Gaussian stationary processeFractional calculuStatistics - ComputationTransfer functionWind speedFractional calculusSuperposition principleSettore ICAR/08 - Scienza Delle CostruzioniComputation (stat.CO)Condensed Matter - Statistical MechanicsLinear filterCivil and Structural EngineeringMathematics
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A comparative analysis of the statistical properties of large mobile phone calling networks.

2014

Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from …

FOS: Computer and information sciencesPhysics - Physics and SocietyChinaComputer scienceFOS: Physical sciencesInformation Storage and RetrievalPhysics and Society (physics.soc-ph)ArticleSocial NetworkingComputer Communication NetworksSocio-technical systemsComputer SimulationProxy (statistics)Human communicationStatisticSocial and Information Networks (cs.SI)MultidisciplinaryModels StatisticalSocial networkbusiness.industryStatistical physicComputer Science - Social and Information NetworksNonlinear phenomenaComplex networkSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Mobile phonebusinessTelecommunicationsCell PhoneScientific reports
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Probabilistic Memristive Networks: Application of a Master Equation to Networks of Binary ReRAM cells

2020

Abstract The possibility of using non-deterministic circuit components has been gaining significant attention in recent years. The modeling and simulation of their circuits require novel approaches, as now the state of a circuit at an arbitrary moment in time cannot be predicted deterministically. Generally, these circuits should be described in terms of probabilities, the circuit variables should be calculated on average, and correlation functions should be used to explore interrelations among the variables. In this paper, we use, for the first time, a master equation to analyze the networks composed of probabilistic binary memristors. Analytical solutions of the master equation for the ca…

FOS: Computer and information sciencesProbabilistic computingComputer scienceGeneral MathematicsGeneral Physics and AstronomyBinary numberFOS: Physical sciencesComputer Science - Emerging TechnologiesMemristorTopologylaw.inventionModeling and simulationComputer Science::Hardware ArchitectureComputer Science::Emerging TechnologieslawMaster equationMesoscale and Nanoscale Physics (cond-mat.mes-hall)Probabilistic logicElectronic circuitCondensed Matter - Materials ScienceCondensed Matter - Mesoscale and Nanoscale PhysicsApplied MathematicsProbabilistic logicMaterials Science (cond-mat.mtrl-sci)Statistical and Nonlinear PhysicsMoment (mathematics)Emerging Technologies (cs.ET)State (computer science)NetworksMemristors
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A quantum vocal theory of sound

2020

Concepts and formalism from acoustics are often used to exemplify quantum mechanics. Conversely, quantum mechanics could be used to achieve a new perspective on acoustics, as shown by Gabor studies. Here, we focus in particular on the study of human voice, considered as a probe to investigate the world of sounds. We present a theoretical framework that is based on observables of vocal production, and on some measurement apparati that can be used both for analysis and synthesis. In analogy to the description of spin states of a particle, the quantum-mechanical formalism is used to describe the relations between the fundamental states associated with phonetic labels such as phonation, turbule…

FOS: Computer and information sciencesSound (cs.SD)Computer scienceAudio processingAnalogyAudio processing; Quantum-inspired algorithms; Sound representation01 natural sciencesComputer Science - Sound050105 experimental psychologyTheoretical Computer Sciencesymbols.namesakeAudio and Speech Processing (eess.AS)0103 physical sciencesFOS: Electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesPhonationElectrical and Electronic Engineering010306 general physicsQuantumHuman voiceQuantum computerSound representationSettore INF/01 - Informatica05 social sciencesStatistical and Nonlinear PhysicsObservableSettore MAT/04 - Matematiche ComplementariElectronic Optical and Magnetic MaterialsVibrationClassical mechanicsFourier transformComputer Science::SoundModeling and SimulationSignal ProcessingsymbolsQuantum-inspired algorithms Audio processing Sound representationQuantum-inspired algorithmsSettore ING-INF/05 - Sistemi di Elaborazione delle InformazioniElectrical Engineering and Systems Science - Audio and Speech Processing
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Large-scale compression of genomic sequence databases with the Burrows-Wheeler transform

2012

Motivation The Burrows-Wheeler transform (BWT) is the foundation of many algorithms for compression and indexing of text data, but the cost of computing the BWT of very large string collections has prevented these techniques from being widely applied to the large sets of sequences often encountered as the outcome of DNA sequencing experiments. In previous work, we presented a novel algorithm that allows the BWT of human genome scale data to be computed on very moderate hardware, thus enabling us to investigate the BWT as a tool for the compression of such datasets. Results We first used simulated reads to explore the relationship between the level of compression and the error rate, the leng…

FOS: Computer and information sciencesStatistics and ProbabilityBurrows–Wheeler transformComputer scienceData_CODINGANDINFORMATIONTHEORYBurrows-Wheeler transformcomputer.software_genreBiochemistryBurrows-Wheeler transform; Data Compression; Next-generation sequencingComputer Science - Data Structures and AlgorithmsEscherichia coliCode (cryptography)HumansOverhead (computing)Data Structures and Algorithms (cs.DS)Computer SimulationQuantitative Biology - GenomicsMolecular BiologyGenomics (q-bio.GN)Genome HumanString (computer science)Search engine indexingSortingGenomicsSequence Analysis DNAConstruct (python library)Data CompressionComputer Science ApplicationsComputational MathematicsComputational Theory and MathematicsFOS: Biological sciencesNext-generation sequencingData miningDatabases Nucleic AcidcomputerAlgorithmsData compression
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A novel exact representation of stationary colored Gaussian processes (fractional differential approach)

2010

A novel representation of functions, called generalized Taylor form, is applied to the filtering of white noise processes. It is shown that every Gaussian colored noise can be expressed as the output of a set of linear fractional stochastic differential equations whose solution is a weighted sum of fractional Brownian motions. The exact form of the weighting coefficients is given and it is shown that it is related to the fractional moments of the target spectral density of the colored noise.

FOS: Computer and information sciencesStatistics and ProbabilityDifferential equationFOS: Physical sciencesGeneral Physics and AstronomyStatistics - ComputationStochastic differential equationsymbols.namesakeSpectral MomentsApplied mathematicsStationary processeGaussian processCondensed Matter - Statistical MechanicsComputation (stat.CO)Mathematical PhysicsMathematicsGeneralized functionStatistical Mechanics (cond-mat.stat-mech)Statistical and Nonlinear PhysicsMathematical Physics (math-ph)White noiseClosed and exact differential formsColors of noiseGaussian noiseFractional CalculuModeling and SimulationsymbolsSettore ICAR/08 - Scienza Delle Costruzioni
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Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions

2021

We develop a Bayesian inference method for diffusions observed discretely and with noise, which is free of discretisation bias. Unlike existing unbiased inference methods, our method does not rely on exact simulation techniques. Instead, our method uses standard time-discretised approximations of diffusions, such as the Euler--Maruyama scheme. Our approach is based on particle marginal Metropolis--Hastings, a particle filter, randomised multilevel Monte Carlo, and importance sampling type correction of approximate Markov chain Monte Carlo. The resulting estimator leads to inference without a bias from the time-discretisation as the number of Markov chain iterations increases. We give conver…

FOS: Computer and information sciencesStatistics and ProbabilityDiscretizationComputer scienceMarkovin ketjutInference010103 numerical & computational mathematicssequential Monte CarloBayesian inferenceStatistics - Computation01 natural sciencesMethodology (stat.ME)010104 statistics & probabilitysymbols.namesakediffuusio (fysikaaliset ilmiöt)FOS: MathematicsDiscrete Mathematics and Combinatorics0101 mathematicsHidden Markov modelComputation (stat.CO)Statistics - Methodologymatematiikkabayesilainen menetelmäApplied MathematicsProbability (math.PR)diffusionmatemaattiset menetelmätMarkov chain Monte CarloMarkov chain Monte CarloMonte Carlo -menetelmätNoiseimportance sampling65C05 (primary) 60H35 65C35 65C40 (secondary)Modeling and Simulationsymbolsmatemaattiset mallitStatistics Probability and Uncertaintymultilevel Monte CarloParticle filterAlgorithmMathematics - ProbabilityImportance samplingSIAM/ASA Journal on Uncertainty Quantification
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Reliability analysis of processes with moving cracked material

2015

Abstract The reliability of processes with moving elastic and isotropic material containing initial cracks is considered in terms of fracture. The material is modelled as a moving plate which is simply supported from two of its sides and subjected to homogeneous tension acting in the travelling direction. For tension, two models are studied: (i) tension is constant with respect to time, and (ii) tension varies temporally according to an Ornstein–Uhlenbeck process. Cracks of random length are assumed to occur in the material according to a stochastic counting process. For a general counting process, a representation of the nonfracture probability of the system is obtained that exploits condi…

FOS: Computer and information sciencesStochastic modellingBoundary (topology)02 engineering and technologyComputational Engineering Finance and Science (cs.CE)0203 mechanical engineeringfirst passage timeComputer Science - Computational Engineering Finance and Sciencestochastic modelMathematics040101 forestryta214Counting processTension (physics)Applied Mathematicsta111Mathematical analysisIsotropyOrnstein–Uhlenbeck process04 agricultural and veterinary sciencesmoving material020303 mechanical engineering & transportsfractureModeling and Simulation0401 agriculture forestry and fisheriesOrnstein-Uhlenbeck processFirst-hitting-time modelConstant (mathematics)Applied Mathematical Modelling
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Random Walk in a N-cube Without Hamiltonian Cycle to Chaotic Pseudorandom Number Generation: Theoretical and Practical Considerations

2017

Designing a pseudorandom number generator (PRNG) is a difficult and complex task. Many recent works have considered chaotic functions as the basis of built PRNGs: the quality of the output would indeed be an obvious consequence of some chaos properties. However, there is no direct reasoning that goes from chaotic functions to uniform distribution of the output. Moreover, embedding such kind of functions into a PRNG does not necessarily allow to get a chaotic output, which could be required for simulating some chaotic behaviors. In a previous work, some of the authors have proposed the idea of walking into a $\mathsf{N}$-cube where a balanced Hamiltonian cycle has been removed as the basis o…

FOS: Computer and information sciencesUniform distribution (continuous)Computer Science - Cryptography and SecurityComputer scienceHamiltonian CycleChaoticPseudorandom Numbers GeneratorFOS: Physical sciences02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]01 natural sciencesUpper and lower bounds[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computingsymbols.namesake[INFO.INFO-MC]Computer Science [cs]/Mobile Computing[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0202 electrical engineering electronic engineering information engineeringApplied mathematics[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]0101 mathematicsEngineering (miscellaneous)Pseudorandom number generatorChaotic IterationsBasis (linear algebra)Applied Mathematics020208 electrical & electronic engineering010102 general mathematicsRandom walkNonlinear Sciences - Chaotic DynamicsHamiltonian path[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationNonlinear Sciences::Chaotic Dynamics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Modeling and SimulationRandom Walk[NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]symbolsPseudo random number generator[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Chaotic Dynamics (nlin.CD)[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Cryptography and Security (cs.CR)
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