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showing 10 items of 3931 documents

Role of noise in a market model with stochastic volatility

2006

We study a generalization of the Heston model, which consists of two coupled stochastic differential equations, one for the stock price and the other one for the volatility. We consider a cubic nonlinearity in the first equation and a correlation between the two Wiener processes, which model the two white noise sources. This model can be useful to describe the market dynamics characterized by different regimes corresponding to normal and extreme days. We analyze the effect of the noise on the statistical properties of the escape time with reference to the noise enhanced stability (NES) phenomenon, that is the noise induced enhancement of the lifetime of a metastable state. We observe NES ef…

Noise inducedProbability theory stochastic processes and statisticFOS: Physical sciencesEconomicFOS: Economics and businessStochastic differential equationStatistical physicsMarket modelCondensed Matter - Statistical MechanicsEconomics; econophysics financial markets business and management; Probability theory stochastic processes and statistics; Fluctuation phenomena random processes noise and Brownian motion; Complex SystemsMathematicsFluctuation phenomena random processes noise and Brownian motionStatistical Finance (q-fin.ST)Stochastic volatilityStatistical Mechanics (cond-mat.stat-mech)Cubic nonlinearityQuantitative Finance - Statistical FinanceComplex SystemsWhite noiseDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksCondensed Matter PhysicsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Electronic Optical and Magnetic MaterialsHeston modelVolatility (finance)econophysics financial markets business and management
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A “Noise Gene” for Econets

1993

Genetically controlled noise is applied to the weights of neural networks trained with a genetic algorithm. Networks simulate simple organisms living in an environment Reproduction is based on the ability of each network, during its life, to respond to sensory information from the environment with appropriate motor action. Each network has an amount of noise which is genetically inherited (in the ‘noise gene’) with mutations and it varies interindividually. Noise modifies the value of a weight differently for each spreading of the activation through the network. Such noise has a positive effect on the evolutionary increase in fitness and it makes fitness less dependent on the initial choice…

NoiseArtificial neural networkComputer scienceGenetic algorithmProcess (computing)Motor actionBiological systemRandom populationGene
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Probabilistic Analysis of Non-Local 1-D Continuum under Random Load

2008

Non-Local Mechanics Probabilistic Analysis Random LoadsSettore ICAR/08 - Scienza Delle Costruzioni
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Medium-chain triglycerides may improve memory in non-demented older adults: a systematic review of randomized controlled trials

2022

Abstract Background Ketosis has been exploited for its neuroprotective impact and treatment of neurological conditions via ketone production. Exogenous medium-chain triglyceride (MCT) supplementation may induce nutritional ketosis. The aim of this systematic review is to explore the effects of MCTs on memory function in older adults without cognitive impairment. Methods A systematic literature search of PubMed, Cochrane Library, Scopus, and Web of Science was employed from inception until April 2022 for randomized controlled trials (RCTs) in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, investigating the impact of MCT oils on com…

Non-demented1106 Human Movement and Sports Sciences1103 Clinical SciencesKetone BodiesKetosisMedium-chain triglyceridesNutritional ketosisMemoryGeriatricsVDP::Medisinske Fag: 700::Klinisk medisinske fag: 750::Geriatri: 778HumansCognitive functionGeriatrics and GerontologyOilsTriglyceridesAgedRandomized Controlled Trials as TopicBMC geriatrics
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Nonalcoholic steatohepatitis: the therapeutic challenge of a global epidemic.

2011

Nonalcoholic fatty liver (NAFL) and especially its inflammatory variant nonalcoholic steatohepatitis (NASH) have become a major challenge to healthcare systems worldwide because of the increasing prevalence of its major risk factors obesity and type 2 diabetes, which are closely linked to overeating, physical inactivity, and the metabolic syndrome.Between 10 and 20% of patients with NAFL develop NASH, which can progress to cirrhosis, end-stage liver disease, and hepatocellular carcinoma. The overall mortality in these patients is significantly increased because of both cardiovascular and liver-related complications. Sustained weight loss by diet and exercise, which is the most effective the…

Nonalcoholic steatohepatitisDiet ReducingEndocrinology Diabetes and MetabolismAnti-Inflammatory AgentsType 2 diabetesBioinformaticsBile Acids and SaltsNon-alcoholic Fatty Liver DiseaseGeneticsmedicineAnimalsHumansHypoglycemic AgentsObesityEpidemicsMolecular BiologyRandomized Controlled Trials as TopicNutrition and Dieteticsbusiness.industryFatty liverCell Biologymedicine.diseaseObesityFatty LiverHydroxymethylglutaryl-CoA Reductase InhibitorsCardiology and Cardiovascular MedicinebusinessHealthcare systemCurrent opinion in lipidology
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Active Learning of Recursive Functions by Ultrametric Algorithms

2014

We study active learning of classes of recursive functions by asking value queries about the target function f, where f is from the target class. That is, the query is a natural number x, and the answer to the query is f(x). The complexity measure in this paper is the worst-case number of queries asked. We prove that for some classes of recursive functions ultrametric active learning algorithms can achieve the learning goal by asking significantly fewer queries than deterministic, probabilistic, and even nondeterministic active learning algorithms. This is the first ever example of a problem where ultrametric algorithms have advantages over nondeterministic algorithms.

Nondeterministic algorithmTheoretical computer scienceActive learning (machine learning)Probabilistic logicNatural numberFunction (mathematics)Inductive reasoningUltrametric spaceAlgorithmMathematicsRandomized algorithm
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PARAMETRIC SELF-TRAPPING OF OPTICAL BEAMS VIA RANDOM QUASI PHASE MATCHING IN LITHIUM TANTALATE WAVEGUIDE

2011

We report on experimental evidence of parametric spatial solitons in a lithium tantalate waveguide with randomized periodic ferroelectric poling. Two-color self-focusing via quadratic cascading overcomes the diffractive nature of both fundamental and frequency-doubled beams.

Nonlinear optics Parametric solitons Random quasi-phase-matchingSettore ING-INF/02 - Campi ElettromagneticiSettore ING-INF/01 - Elettronica
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MAPPATURA DEL DISORDINE NON LINEARE MEDIANTE INTERAZIONE PARAMETRICA A TRE ONDE

2010

We introduce a simple approach for characterizing the ferroelectric domain distribution in bulk quadratic crystals. The approach is demonstrated in a lithium tantalate sample with periodic electric field poling and random mark-to-space ratio.

Nonlinear optics Random quasi-phase-matching Image analysis
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Random attractors for stochastic lattice systems with non-Lipschitz nonlinearity

2011

In this article, we study the asymptotic behaviour of solutions of a first-order stochastic lattice dynamical system with an additive noise. We do not assume any Lipschitz condition on the nonlinear term, just a continuity assumption together with growth and dissipative conditions so that uniqueness of the Cauchy problem fails to be true. Using the theory of multi-valued random dynamical systems, we prove the existence of a random compact global attractor.

Nonlinear systemAlgebra and Number TheoryApplied MathematicsMathematical analysisAttractorDissipative systemRandom compact setInitial value problemUniquenessRandom dynamical systemLipschitz continuityAnalysisMathematicsJournal of Difference Equations and Applications
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Identification of Nonlinear Systems Described by Hammerstein Models

2004

This paper deals with a method for identification of nonlinear systems suitable to be described by Hammerstein models consisting of a static nonlinearity followed by an ARX linear model. The estimation of the static nonlinearity is carried out supplying the system with a sequence of step signals of various amplitude and determining the corresponding steady-state responses. The estimation of the parameters of the ARX linear system is carried out by means of a least square estimator using data generated supplying the system with a Pseudorandom Binary Sequence (PRBS). The method in question is able to identify static nonlinearities of general type, also with hysteresis and/or discontinuities. …

Nonlinear systemSequenceAmplitudeSettore ING-INF/04 - AutomaticaControl theoryLinear systemLinear modelEstimatorClassification of discontinuitiesPseudorandom binary sequenceMathematicsHammerstein models identification nonlinear systems
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