Search results for "Stochastic Proce"

showing 10 items of 349 documents

Local Granger causality

2021

Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. For Gaussian variables it is equivalent to transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes. We exploit such equivalence and calculate exactly the 'local Granger causality', i.e. the profile of the information transfer at each discrete time point in Gaussian processes; in this frame Granger causality is the average of its local version. Our approach offers a robust and computationally fast method to follow the information transfer along the time history of linear stochastic processes, as well as of nonlinear …

FOS: Computer and information sciencesInformation transferGaussianFOS: Physical sciencestechniques; information theory; granger causalityMachine Learning (stat.ML)Quantitative Biology - Quantitative Methods01 natural sciences010305 fluids & plasmasVector autoregressionsymbols.namesakegranger causalityGranger causalityStatistics - Machine Learning0103 physical sciencesApplied mathematicstime serie010306 general physicsQuantitative Methods (q-bio.QM)Mathematicsinformation theoryStochastic processDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComputational Physics (physics.comp-ph)Discrete time and continuous timeAutoregressive modelFOS: Biological sciencesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticasymbolsTransfer entropytechniquesPhysics - Computational Physics
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Multiscale analysis of information dynamics for linear multivariate processes.

2016

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving aver…

FOS: Computer and information sciencesInformation transferMultivariate statisticsMultivariate analysisComputer scienceComputer Science - Information Theory0206 medical engineeringStochastic ProcesseBiomedical EngineeringFOS: Physical sciencesInformation Storage and RetrievalHealth Informatics02 engineering and technology01 natural sciencesEntropy (classical thermodynamics)Moving average0103 physical sciencesEntropy (information theory)Computer SimulationStatistical physicsEntropy (energy dispersal)Time series010306 general physicsEntropy (arrow of time)Multivariate Analysi1707Stochastic ProcessesEntropy (statistical thermodynamics)Stochastic processInformation Theory (cs.IT)Probability and statisticsModels Theoretical020601 biomedical engineeringComplex dynamicsAutoregressive modelPhysics - Data Analysis Statistics and ProbabilitySignal ProcessingSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaMultivariate AnalysisData Analysis Statistics and Probability (physics.data-an)Entropy (order and disorder)Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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Online shortest paths with confidence intervals for routing in a time varying random network

2018

International audience; The increase in the world's population and rising standards of living is leading to an ever-increasing number of vehicles on the roads, and with it ever-increasing difficulties in traffic management. This traffic management in transport networks can be clearly optimized by using information and communication technologies referred as Intelligent Transport Systems (ITS). This management problem is usually reformulated as finding the shortest path in a time varying random graph. In this article, an online shortest path computation using stochastic gradient descent is proposed. This routing algorithm for ITS traffic management is based on the online Frank-Wolfe approach.…

FOS: Computer and information sciencesMathematical optimizationComputer sciencePopulation02 engineering and technology[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE][INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing[SPI]Engineering Sciences [physics][INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR]0502 economics and business11. SustainabilityComputer Science - Data Structures and Algorithms0202 electrical engineering electronic engineering information engineeringFOS: MathematicsData Structures and Algorithms (cs.DS)educationIntelligent transportation systemMathematics - Optimization and ControlRandom graph050210 logistics & transportationeducation.field_of_studyStochastic process[SPI.PLASMA]Engineering Sciences [physics]/Plasmas05 social sciencesApproximation algorithm[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationStochastic gradient descentOptimization and Control (math.OC)[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]Shortest path problem020201 artificial intelligence & image processing[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET]Routing (electronic design automation)[INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]
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Classical and Quantum Annealing in the Median of Three Satisfiability

2011

We determine the classical and quantum complexities of a specific ensemble of three-satisfiability problems with a unique satisfying assignment for up to N = 100 and 80 variables, respectively. In the classical limit, we employ generalized ensemble techniques and measure the time that a Markovian Monte Carlo process spends in searching classical ground states. In the quantum limit, we determine the maximum finite correlation length along a quantum adiabatic trajectory determined by the linear sweep of the adiabatic control parameter in the Hamiltonian composed of the problem Hamiltonian and the constant transverse field Hamiltonian. In the median of our ensemble, both complexities diverge e…

FOS: Computer and information sciencesPolynomialComputational complexity theoryQuantum dynamicsFOS: Physical sciencesComputational Complexity (cs.CC)Classical limitClassical capacityQuantum mechanicsddc:530Statistical physicsALGORITHMAmplitude damping channelQuantumQuantum fluctuationCondensed Matter - Statistical MechanicsMathematicsPhysicsQuantum PhysicsStatistical Mechanics (cond-mat.stat-mech)Stochastic processQuantum annealingAdiabatic quantum computationAtomic and Molecular Physics and OpticsSatisfiabilityJComputer Science - Computational ComplexityComputerSystemsOrganization_MISCELLANEOUSQuantum algorithmPHASE-TRANSITIONSQuantum dissipationQuantum Physics (quant-ph)
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Progressive Stochastic Binarization of Deep Networks

2019

A plethora of recent research has focused on improving the memory footprint and inference speed of deep networks by reducing the complexity of (i) numerical representations (for example, by deterministic or stochastic quantization) and (ii) arithmetic operations (for example, by binarization of weights). We propose a stochastic binarization scheme for deep networks that allows for efficient inference on hardware by restricting itself to additions of small integers and fixed shifts. Unlike previous approaches, the underlying randomized approximation is progressive, thus permitting an adaptive control of the accuracy of each operation at run-time. In a low-precision setting, we match the accu…

FOS: Computer and information sciencesScheme (programming language)Computer Science - Machine LearningComputer scienceStochastic processScalar (physics)Sampling (statistics)Machine Learning (stat.ML)Machine Learning (cs.LG)Statistics - Machine LearningApproximation errorBounded functionReference implementationRepresentation (mathematics)computerAlgorithmcomputer.programming_language2019 Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing - NeurIPS Edition (EMC2-NIPS)
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Tick size and price diffusion

2010

A tick size is the smallest increment of a security price. It is clear that at the shortest time scale on which individual orders are placed the tick size has a major role which affects where limit orders can be placed, the bid-ask spread, etc. This is the realm of market microstructure and there is a vast literature on the role of tick size on market microstructure. However, tick size can also affect price properties at longer time scales, and relatively less is known about the effect of tick size on the statistical properties of prices. The present paper is divided in two parts. In the first we review the effect of tick size change on the market microstructure and the diffusion properties…

FOS: Economics and businessStatistical Finance (q-fin.ST)Market microstructureEconophysicsFinancial markets Market microstructure Stochastic processes EconophysicsQuantitative Finance - Statistical FinanceFinancial marketStochastic processe
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How markets slowly digest changes in supply and demand

2008

In this article we revisit the classic problem of tatonnement in price formation from a microstructure point of view, reviewing a recent body of theoretical and empirical work explaining how fluctuations in supply and demand are slowly incorporated into prices. Because revealed market liquidity is extremely low, large orders to buy or sell can only be traded incrementally, over periods of time as long as months. As a result order flow is a highly persistent long-memory process. Maintaining compatibility with market efficiency has profound consequences on price formation, on the dynamics of liquidity, and on the nature of impact. We review a body of theory that makes detailed quantitative pr…

Factor marketPhysics - Physics and Society050208 financeMarket rateQuantitative Finance - Trading and Market MicrostructureStatistical Mechanics (cond-mat.stat-mech)Market clearing05 social sciencesFinancial marketFOS: Physical sciencesMarket microstructurePhysics and Society (physics.soc-ph)Supply and demandMarket liquidityTrading and Market Microstructure (q-fin.TR)MicroeconomicsFOS: Economics and businessFinancial Markets Econophysics Microstructure Stochastic processes0502 economics and businessEconomics050207 economicsMarket impactCondensed Matter - Statistical Mechanics
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A generalized method for the design of ergodic sum-of-cisoids simulators for multiple uncorrelated rayleigh fading channels

2010

In this paper, we present a new method for the design of ergodic sum-of-sinusoids (SOS) simulation models for multiple uncorrelated Rayleigh fading channels. The method, which is intended for a special class of SOS models, known as sum-of-cisoids (SOC) models, can be used to generate an arbitrary number of uncorrelated Rayleigh fading waveforms with specified Doppler power spectral characteristics. This is in contrast to the SOS simulators currently available in the open literature that have been designed under the isotropic scattering assumption, which are limited to the simulation of uncorrelated channels characterized by Clarke's U-shaped Doppler power spectral density (DPSD). The excell…

Fading distributionScatteringStochastic processControl theoryMIMOSpectral densityErgodic theoryData_CODINGANDINFORMATIONTHEORYCommunications systemAlgorithmComputer Science::Information TheoryMathematicsRayleigh fading2010 4th International Conference on Signal Processing and Communication Systems
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Seismically induced, non-stationary hydrodynamic pressure in a dam-reservoir system

2003

Stochastic seismic analysis of hydrodynamic pressure in a dam-reservoir system is presented in this paper. The analysis is conducted assuming infinite reservoir compressible fluid and modeling seismic acceleration as a normal zero-mean stochastic process obtained by Penzien filter. The non-homogeneous boundary conditions associated to the problem have been incorporated into the equation of pressure wave scattering in the form of a forcing function turning the non-homogeneous boundary value problem into an homogeneous one. Solution obtained via modal analysis in time-domain is coupled with the use of classical Ito stochastic differential calculus to characterize the stochastic hydrodynamic p…

Field (physics)Stochastic processModal analysisMechanical EngineeringAerospace EngineeringOcean EngineeringStatistical and Nonlinear PhysicsMechanicsCondensed Matter PhysicsCompressible flowPhysics::GeophysicsSeismic analysisAccelerationFilter (large eddy simulation)Nuclear Energy and EngineeringGeotechnical engineeringBoundary value problemGeologyCivil and Structural EngineeringProbabilistic Engineering Mechanics
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Stability in a System subject to Noise with Regulated Periodicity

2011

The stability of a simple dynamical system subject to multiplicative one-side pulse noise with hidden periodicity is investigated both analytically and numerically. The stability analysis is based on the exact result for the characteristic functional of the renewal pulse process. The influence of the memory effects on the stability condition is analyzed for two cases: (i) the dead-time-distorted poissonian process, and (ii) the renewal process with Pareto distribution. We show that, for fixed noise intensity, the system can be stable when the noise is characterized by high periodicity and unstable at low periodicity.

Fluctuation phenomena random processes noise and Brownian motionPeriodicityStochastic processProbability theory stochastic processes and statisticStochastic analysis methodsOrnstein–Uhlenbeck processModels TheoreticalStability (probability)Settore FIS/03 - Fisica Della MateriaStable processsymbols.namesakeStochastic differential equationNoiseControl theorysymbolsPareto distributionRenewal theoryStatistical physicsMathematics
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