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Galerkin Solution of Stochastic Beam Bending on Winkler Foundations

SILVA, C. R. A.; HEUSI, H. P. Azikri de; MANTOVANI, G. E.; BECK, A. T.
Fonte: TECH SCIENCE PRESS Publicador: TECH SCIENCE PRESS
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
56.04%
In this paper, the Askey-Wiener scheme and the Galerkin method are used to obtain approximate solutions to stochastic beam bending on Winkler foundation. The study addresses Euler-Bernoulli beams with uncertainty in the bending stiffness modulus and in the stiffness of the foundation. Uncertainties are represented by parameterized stochastic processes. The random behavior of beam response is modeled using the Askey-Wiener scheme. One contribution of the paper is a sketch of proof of existence and uniqueness of the solution to problems involving fourth order operators applied to random fields. From the approximate Galerkin solution, expected value and variance of beam displacement responses are derived, and compared with corresponding estimates obtained via Monte Carlo simulation. Results show very fast convergence and excellent accuracies in comparison to Monte Carlo simulation. The Askey-Wiener Galerkin scheme presented herein is shown to be a theoretically solid and numerically efficient method for the solution of stochastic problems in engineering.; Sao Paulo State Foundation for Research - FAPESP[2008/10366-4]; National Council for Research and Development - CNPq[305120/2006-9]

SELF-SIMILARITY AND LAMPERTI CONVERGENCE FOR FAMILIES OF STOCHASTIC PROCESSES

JORGENSEN, Bent; MARTINEZ, Jose R.; DEMETRIO, Clarice G. B.
Fonte: SPRINGER Publicador: SPRINGER
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
56.11%
We define a new type of self-similarity for one-parameter families of stochastic processes, which applies to certain important families of processes that are not self-similar in the conventional sense. This includes Hougaard Levy processes such as the Poisson processes, Brownian motions with drift and the inverse Gaussian processes, and some new fractional Hougaard motions defined as moving averages of Hougaard Levy process. Such families have many properties in common with ordinary self-similar processes, including the form of their covariance functions, and the fact that they appear as limits in a Lamperti-type limit theorem for families of stochastic processes.; Danish Natural Science Research Council; FAPESP, Brazil

Modelagem de séries temporais financeiras multidimensionais via processos estocásticos e cópulas de Lévy ; Multidimensional Financial Time Series Modelling via Lévy Stochastic Processes and Copulas

Santos, Edson Bastos e
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 16/12/2005 PT
Relevância na Pesquisa
66.14%
O principal objetivo deste estudo é descrever modelos para séries temporais de ativos financeiros que sejam robustos às tradicionais hipóteses: distribuição gaussiana e continuidade. O primeiro capítulo está preocupado em apresentar, de uma maneira geral, os conceitos matemáticos mais importantes relacionadas a processos estocásticos e difusões. O segundo capítulo trata de processos de incrementos independentes e estacionários, i.e., processos de Lévy, suas trajetórias estocásticas, propriedades distribucionais e, a relação entre processos markovianos e martingales. Alguns dos resultados apresentados neste capítulo são: a estrutura e as propriedades dos processos compostos de Poisson, medida de Lévy, decomposição de Lévy-Itô e representação de Lévy-Khinchin. O terceiro capítulo mostra como construir processos de Lévy por meio de transformações lineares, inclinação da medida de Lévy e subordina ção. Uma atenção especial é dada aos processos subordinados, tais como os modelos variância gama, normal gaussiana invertida e hiperbólico generalizado. Neste capítulo também é apresentado um exemplo pragmático com dados brasileiros de estimação de parâmetros por meio do método de máxima Verossimilhança. O quarto capítulo é devotado aos modelos multidimensionais e...

Aspectos dos Fundamentos da Mecânica Quântica: Processos Estocásticos e Analogia com Turbulência; Aspects of the foundations of quantum mechanics: stochastic processes and analogy with turbulence.

Santos, Léa Ferreira dos
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 10/08/2000 PT
Relevância na Pesquisa
56.01%
Nesta tese apresentamos algumas possíveis interpretações para a descrição dos fenômenos quânticos. Fazemos uso da interpretação estocástica de Nelson para descrever uma corda bosônica aberta e mostramos que os resultados coincidem com aqueles obtidos via primeira quantização. Combinamos ainda esta interpretação, que lida com a posição da partícula, com um particular modelo de localização da função de onda conhecido como CSL, o que nos permite analisar a influência da evolução da função de onda sobre o movimento da partícula. A função de onda desses modelos de redução realiza um movimento estocástico no espaço de Hilbert devido à adição de um ruído multiplicativo na equação de Schrödinger. Mostramos que a partícula, por sua vez, sofre movimento turbulento, o que motiva uma analogia entre sistemas quânticos abertos e turbulência, de forma semelhante à que já havia sido realizada entre sistemas quânticos isolados e movimento browniano.; In this thesis we present some possible interpretations for the description of quantum phenomena. We make use of Nelson's stochastic interpretation to describe an open bosonic string and show that the results coincide with those obtained from the first quantization. Moreover...

Modelo de predição de falhas baseado em processos estocásticos e filtragem Kalman para suporte à manutenção preditiva de sistemas elétricos, eletrônicos e programáveis.; Fault prediction model based on stochastic processes and Kalman filtering aiming to support predictive maintenance procedures of electrical, electronic and programmable systems.

Silva Neto, Antonio Vieira da
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 09/06/2014 PT
Relevância na Pesquisa
66.02%
Com o aumento do uso de sistemas elétricos, eletrônicos e programáveis em aplicações de diversos domínios, tais como entretenimento, realização de transações financeiras, distribuição de energia elétrica, controle de processos industriais e sinalização e controle em transporte de passageiros e carga, é essencial que as políticas de manutenção utilizadas sejam capazes de minimizar os custos associados a eventuais falhas que afetem negativamente os serviços providos. Ao longo das últimas décadas, foi sedimentada a tendência de que a adoção de técnicas de manutenção preditiva representa uma das abordagens mais viáveis e promissoras para que falhas de sistemas utilizados em diversas aplicações possam ser detectadas antes de elas efetivamente ocorrerem. Considerando-se que uma parcela significativa dos estudos recentes na área de manutenção preditiva de sistemas apresenta como limitação o custo elevado para se instalar uma infraestrutura específica para realizar a coleta de dados que serão usados para dar suporte à predição das falhas futuras de um sistema, o modelo proposto no presente estudo visa permitir que os índices de dependabilidade e as falhas futuras de sistemas elétricos, eletrônicos e programáveis sejam estimados utilizando-se dados já disponíveis de falhas e manutenções passadas. Para tanto...

Information geometric similarity measurement for near-random stochastic processes

Dodson, C.T.J.; Scharcanski, Jacob
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Artigo de Revista Científica Formato: application/pdf
ENG
Relevância na Pesquisa
56.06%
We outline the information-theoretic differential geometry of gamma distributions, which contain exponential distributions as a special case, and log-gamma distributions. Our arguments support the opinion that these distributions have a natural role in representing departures from randomness, uniformity, and Gaussian behavior in stochastic processes. We show also how the information geometry provides a surprisingly tractable Riemannian manifold and product spaces thereof, on which may be represented the evolution of a stochastic process, or the comparison of different processes, by means of well-founded maximum likelihood parameter estimation. Our model incorporates possible correlations among parameters. We discuss applications and provide some illustrations from a recent study of amino acid self-clustering in protein sequences; we provide also some results from simulations for multisymbol sequences.

Stochastic field processes in the mathematical modelling of damped transmission line vibrations

Hagedorn, P.; Schmidt, J.; Nascimento, N.
Fonte: Universidade Estadual Paulista Publicador: Universidade Estadual Paulista
Tipo: Artigo de Revista Científica Formato: 359-363
ENG
Relevância na Pesquisa
56.02%
Wind-excited vibrations in the frequency range of 10 to 50 Hz due to vortex shedding often cause fatigue failures in the cables of overhead transmission lines. Damping devices, such as the Stockbridge dampers, have been in use for a long time for supressing these vibrations. The dampers are conveniently modelled by means of their driving point impedance, measured in the lab over the frequency range under consideration. The cables can be modelled as strings with additional small bending stiffness. The main problem in modelling the vibrations does however lay in the aerodynamic forces, which usually are approximated by the forces acting on a rigid cylinder in planar flow. In the present paper, the wind forces are represented by stochastic processes with arbitrary crosscorrelation in space; the case of a Kármán vortex street on a rigid cylinder in planar flow is contained as a limit case in this approach. The authors believe that this new view of the problem may yield useful results, particularly also concerning the reliability of the lines and the probability of fatigue damages. © 1987.

Stochastic processes in networks of queues with exponential service times and only one class of customers

Ferreira, Manuel Alberto M.
Fonte: Hikari, Ltd Publicador: Hikari, Ltd
Tipo: Artigo de Revista Científica
Publicado em //2014 ENG
Relevância na Pesquisa
66.02%
Two networks of queues models, presented initially by Jackson, in the open case, and Gordon and Newell, in the closed case, stochastic processes are presented and studied in some of their details and problems. The service times are exponentially distributed and there is only one class of customers.

BACKWARD ESTIMATION OF STOCHASTIC PROCESSES WITH FAILURE EVENTS AS TIME ORIGINS1

Gary Chan, Kwun Chuen; Wang, Mei-Cheng
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
Publicado em 01/09/2010 EN
Relevância na Pesquisa
46.13%
Stochastic processes often exhibit sudden systematic changes in pattern a short time before certain failure events. Examples include increase in medical costs before death and decrease in CD4 counts before AIDS diagnosis. To study such terminal behavior of stochastic processes, a natural and direct way is to align the processes using failure events as time origins. This paper studies backward stochastic processes counting time backward from failure events, and proposes one-sample nonparametric estimation of the mean of backward processes when follow-up is subject to left truncation and right censoring. We will discuss benefits of including prevalent cohort data to enlarge the identifiable region and large sample properties of the proposed estimator with related extensions. A SEER–Medicare linked data set is used to illustrate the proposed methodologies.

Disentangling the importance of ecological niches from stochastic processes across scales

Chase, Jonathan M.; Myers, Jonathan A.
Fonte: The Royal Society Publicador: The Royal Society
Tipo: Artigo de Revista Científica
Publicado em 27/08/2011 EN
Relevância na Pesquisa
46.2%
Deterministic theories in community ecology suggest that local, niche-based processes, such as environmental filtering, biotic interactions and interspecific trade-offs largely determine patterns of species diversity and composition. In contrast, more stochastic theories emphasize the importance of chance colonization, random extinction and ecological drift. The schisms between deterministic and stochastic perspectives, which date back to the earliest days of ecology, continue to fuel contemporary debates (e.g. niches versus neutrality). As illustrated by the pioneering studies of Robert H. MacArthur and co-workers, resolution to these debates requires consideration of how the importance of local processes changes across scales. Here, we develop a framework for disentangling the relative importance of deterministic and stochastic processes in generating site-to-site variation in species composition (β-diversity) along ecological gradients (disturbance, productivity and biotic interactions) and among biogeographic regions that differ in the size of the regional species pool. We illustrate how to discern the importance of deterministic processes using null-model approaches that explicitly account for local and regional factors that inherently create stochastic turnover. By embracing processes across scales...

Gene regulation and noise reduction by coupling of stochastic processes

Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
46.13%
Here we characterize the low noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the the two gene states depends on protein number. This fact has a very important implication: there exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.

Exact solution to the stochastic spread of social contagion - using rumours.

Dickinson, Rowland Ernest
Fonte: Universidade de Adelaide Publicador: Universidade de Adelaide
Tipo: Tese de Doutorado
Publicado em //2008
Relevância na Pesquisa
46.15%
This Thesis expands on the current developments of the theory of stochastic diffusion processes of rumours. This is done by advancing the current mathematical characterisation of the solution to the Daley-Kendall model of the simple S-I-R rumour to a physical solution of the sub-population distribution over time of the generalised simple stochastic spreading process in social situations. After discussing stochastic spreading processes in social situations such as the simple epidemic, the simple rumour, the spread of innovations and ad hoc communications networks, it uses the three sub-population simple rumour to develop the theory for the identification of the exact sub-population distribution over time. This is done by identifying the generalised form of the Laplace Transform Characterisation of the solution to the three sub-population single rumour process and the inverse Laplace Transform of this characterisation. In this discussion the concept of the Inter-Changeability Principle is introduced. The general theory is validated for the three population Daley-Kendall Rumour Model and results for the three, five and seven population Daley-Kendall Rumour Models are pre- sented and discussed. The α - p model results for pseudo-Maki-Thompson Models are presented and discussed. In subsequent discussion it presents for the first time a statement of the Threshold Problem for Stochastic Spreading Processes in Social settings as well as stating the associated Threshold Theorem. It also investigates limiting conditions. Aspects of future research resulting from the extension of the three subpopulation model to more than three subpopulations are discussed at the end of the thesis. The computational demands of applying the theory to more than three subpopulations are restrictive; the size of the total population that can be considered at one time is considerably reduced. To retain the ability to compute a large population size...

Optimal Sampling Strategies for Multiscale Stochastic Processes

Ribeiro, Vinay Joseph; Riedi, Rudolf H.; Baraniuk, Richard G.; Ribeiro, Vinay Joseph; Riedi, Rudolf H.; Baraniuk, Richard G.
Fonte: Universidade Rice Publicador: Universidade Rice
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
66.15%
Journal Paper; This paper studies multiscale stochastic processes which are random processes organized on the nodes of a tree. The random variables at different levels on the tree represent time series of samples of a stochastic process at different temporal or spatial cales. We focus on classes of multiscale processes with additional statistical structure connecting scales and seek an optimal linear estimator of coarse scale nodes using an incomplete set of nodes at a finer time scale. We prove that the optimal solution for any tree with so-called independent innovations is readily given by a polynomial-time algorithm which we term the water-filling algorithm. The optimal solutions vary dramatically with the correlation structure of the multiscale process. For so-called scale-invariant trees and processes with positive correlation progression through scales, uniformly spaced leaves are optimal and clustered leaves are the worst possible. For processes with negative correlation progression, uniformly spaced leaves are the worst possible. Our results have implications for network traffic estimation, sensor network design, and environmental monitoring.

Derivation of response spectrum compatible non-stationary stochastic processes relying on Monte Carlo-based peak factor estimation

Giaralis, Agathoklis; Spanos, Pol D.
Fonte: Universidade Rice Publicador: Universidade Rice
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
46.19%
In this paper a novel non-iterative approach is proposed to address the problem of deriving non-stationary stochastic processes which are compatible in the mean sense with a given (target) response (uniform hazard) spectrum (UHS) as commonly desired in the aseismic structural design regulated by contemporary codes of practice. This is accomplished by solving a standard over-determined minimization problem in conjunction with appropriate median peak factors. These factors are determined by a plethora of reported new Monte Carlo studies which on their own possess considerable stochastic dynamics merit. In the proposed approach, generation and treatment of samples of the processes individually on a deterministic basis is not required as is the case with the various approaches found in the literature addressing the herein considered task. The applicability and usefulness of the approach is demonstrated by furnishing extensive numerical data associated with the elastic design UHS of the current European (EC8) and the Chinese (GB 50011) aseismic code provisions. Purposely, simple and thus attractive from a practical viewpoint, uniformly modulated processes assuming either the Kanai-Tajimi (KT) or the Clough-Penzien (C-P) spectral form are employed. The Monte Carlo studies yield damping and duration dependent median peak factor spectra...

A note on three stochastic processes with immigration

Gani, Joseph; Stals, Linda
Fonte: Australian Mathematical Society Publicador: Australian Mathematical Society
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
55.99%
Three stochastic processes, the birth, death and birth-death processes, subject to immigration can be decomposed into the sum of each process in the absence of immigration and an independent process. We examine these independent processes through their pr

A unified formulation of Gaussian vs. sparse stochastic processes - Part I: Continuous-domain theory

Unser, Michael; Tafti, Pouya D.; Sun, Qiyu
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46.15%
We introduce a general distributional framework that results in a unifying description and characterization of a rich variety of continuous-time stochastic processes. The cornerstone of our approach is an innovation model that is driven by some generalized white noise process, which may be Gaussian or not (e.g., Laplace, impulsive Poisson or alpha stable). This allows for a conceptual decoupling between the correlation properties of the process, which are imposed by the whitening operator L, and its sparsity pattern which is determined by the type of noise excitation. The latter is fully specified by a Levy measure. We show that the range of admissible innovation behavior varies between the purely Gaussian and super-sparse extremes. We prove that the corresponding generalized stochastic processes are well-defined mathematically provided that the (adjoint) inverse of the whitening operator satisfies some Lp bound for p>=1. We present a novel operator-based method that yields an explicit characterization of all Levy-driven processes that are solutions of constant-coefficient stochastic differential equations. When the underlying system is stable, we recover the family of stationary CARMA processes, including the Gaussian ones. The approach remains valid when the system is unstable and leads to the identification of potentially useful generalizations of the Levy processes...

Analyzing long-term correlated stochastic processes by means of recurrence networks: Potentials and pitfalls

Zou, Yong; Donner, Reik V.; Kurths, Jürgen
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 11/09/2014
Relevância na Pesquisa
46.15%
Long-range correlated processes are ubiquitous, ranging from climate variables to financial time series. One paradigmatic example for such processes is fractional Brownian motion (fBm). In this work, we highlight the potentials and conceptual as well as practical limitations when applying the recently proposed recurrence network (RN) approach to fBm and related stochastic processes. In particular, we demonstrate that the results of a previous application of RN analysis to fBm (Liu \textit{et al.,} Phys. Rev. E \textbf{89}, 032814 (2014)) are mainly due to an inappropriate treatment disregarding the intrinsic non-stationarity of such processes. Complementarily, we analyze some RN properties of the closely related stationary fractional Gaussian noise (fGn) processes and find that the resulting network properties are well-defined and behave as one would expect from basic conceptual considerations. Our results demonstrate that RN analysis can indeed provide meaningful results for stationary stochastic processes, given a proper selection of its intrinsic methodological parameters, whereas it is prone to fail to uniquely retrieve RN properties for non-stationary stochastic processes like fBm.; Comment: 8 pages, 6 figures

Stationarity of Stochastic Processes In The Fractional Fourier Domains

Shafie, Ahmed El; Khattab, Tamer
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
46.16%
In this paper, we investigate the stationarity of stochastic processes in the fractional Fourier domains. We study the stationarity of a stochastic process after performing fractional Fourier transform (FRFT), and discrete fractional Fourier transform (DFRT) on both continuous and discrete stochastic processes, respectively. Also we investigate the stationarity of the fractional Fourier series (FRFS) coefficients of a continuous time stochastic process, and the stationarity of the discrete time fractional Fourier transform (DTFRFT) of a discrete time stochastic process. Closed formulas of the input process autocorrelation function and pseudo-autocorrelation function after performing the fractional Fourier transform are derived given that the input is a stationary stochastic process. We derive a formula for the output autocorrelation as a function of the $a^{th}$ power spectral density of the input stochastic process, also we derived a formula for the input fractional power spectral density as a function of the fractional Fourier transform of the output process autocorrelation function. We proved that, the input stochastic process must be zero mean to satisfy a necessary but not a sufficient condition of stationarity in the fractional domains. Closed formulas of the resultant statistics are also shown. It is shown that...

Formalized Quantum Stochastic Processes and Hidden Quantum Models with Applications to Neuron Ion Channel Kinetics

Paris, Alan; Atia, George; Vosoughi, Azadeh; Berman, Stephen
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 30/10/2015
Relevância na Pesquisa
56.07%
A new class of formal latent-variable stochastic processes called hidden quantum models (HQM's) is defined in order to clarify the theoretical foundations of ion channel signal processing. HQM's are based on quantum stochastic processes which formalize time-dependent observation. They allow the calculation of autocovariance functions which are essential for frequency-domain signal processing. HQM's based on a particular type of observation protocol called independent activated measurements are shown to to be distributionally equivalent to hidden Markov models yet without an underlying physical Markov process. Since the formal Markov processes are non-physical, the theory of activated measurement allows merging energy-based Eyring rate theories of ion channel behavior with the more common phenomenological Markov kinetic schemes to form energy-modulated quantum channels. Using the simplest quantum channel model consistent with neuronal membrane voltage-clamp experiments, activation eigenenergies are calculated for the Hodgkin-Huxley K+ and Na+ ion channels. It is also shown that maximizing entropy under constrained activation energy yields noise spectral densities approximating $S(f) \sim 1/f^\alpha$, thus offering a biophysical explanation for the ubiquitous $1/f$-type in neurological signals.

Aggregation of weakly dependent doubly stochastic processes

Fermin, Lisandro J.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 13/05/2008
Relevância na Pesquisa
46.24%
The aim of this paper is to extend the aggregation convergence results given in (Dacunha-Castelle and Fermin 2005, Dacunha-Castelle and Fermin 2008) to doubly stochastic linear and nonlinear processes with weakly dependent innovations. First, we introduce a weak dependence notion for doubly stochastic processes, based in the weak dependence definition given in (Doukhan and Louhichi 1999), and we exhibe several models satisfying this notion, such as: doubly stochastic Volterra processes and doubly stochastic Bernoulli scheme with weakly dependent innovations. Afterwards we derive a central limit theorem for the partial aggregation sequence considering weakly dependent doubly stochastic processes. Finally, show a new SLLN for the covariance function of the partial aggregation process in the case of doubly stochastic Volterra processes with interactive innovations. Keywords: Aggregation, weak dependence, doubly stochastic processes, Volterra processes, Bernoulli shift, TCL, SLLN.; Comment: 33 pages