Search results for "stochastic differential equation"
showing 10 items of 80 documents
A class of stochastic differential equations with non-Lipschitzian coefficients: pathwise uniqueness and no explosion
2003
Abstract A new result for the pathwise uniqueness of solutions of stochastic differential equations with non-Lipschitzian coefficients is established. Furthermore, we prove that the solution has no explosion under the growth ξlogξ. To cite this article: S. Fang, T. Zhang, C. R. Acad. Sci. Paris, Ser. I 337 (2003).
What is Differential Stochastic Calculus?
1999
Some well known concepts of stochastic differential calculus of non linear systems corrupted by parametric normal white noise are here outlined. Ito and Stratonovich integrals concepts as well as Ito differential rule are discussed. Applications to the statistics of the response of some linear and non linear systems is also presented.
Ito and Stratonovich integrals for delta-correlated processes
1993
Abstract In this paper the generalization of the Itd and Stratonovich integrals for the case of non-linear systems excited by parametric delta-correlated processes is presented. This generalization gives a new light on the corrective coefficients in the stochastic differential equations driven by parametric delta-correlated processes. The full significance of these corrective terms is evidenced by means of some examples.
Stochastic Differential Calculus
1993
In many cases of engineering interest it has become quite common to use stochastic processes to model loadings resulting from earthquake, turbulent winds or ocean waves. In these circumstances the structural response needs to be adequately described in a probabilistic sense, by evaluating the cumulants or the moments of any order of the response (see e.g. [1, 2]). In particular, for linear systems excited by normal input, the response process is normal too and the moments or the cumulants up to the second order fully characterize the probability density function of both input and output processes. Many practical problems involve processes which are approximately normal and the effect of the…
Stability under influence of noise with regulated periodicity
2009
A very simple stochastic differential equation with quasi‐periodical multiplicative noise is investigated analytically. For fixed noise intensity the system can be stable at high noise periodicity and unstable at low noise periodicity.
Spatio-temporal behaviour of the deep chlorophyll maximum in Mediterranean Sea: Development of a stochastic model for picophytoplankton dynamics
2013
In this paper, by using a stochastic reaction-diffusion-taxis model, we analyze the picophytoplankton dynamics in the basin of the Mediterranean Sea, characterized by poorly mixed waters. The model includes intraspecific competition of picophytoplankton for light and nutrients. The multiplicative noise sources present in the model account for random fluctuations of environmental variables. Phytoplankton distributions obtained from the model show a good agreement with experimental data sampled in two different sites of the Sicily Channel. The results could be extended to analyze data collected in different sites of the Mediterranean Sea and to devise predictive models for phytoplankton dynam…
A non-homogeneous Poisson based model for daily rainfall data
2007
In this paper we report some results of the application of a new stochastic model applied to rainfall daily data. The Poisson models, characterized only by the expected rate of events (impulse occurrences, that is the mean number of impulses per unit time) and the assigned probability distribution of the phenomenon magnitude, do not take into consideration the datum regarding the duration of the occurrences, that is fundamental from a hydrological point of view. In order to describe the phenomenon in a way more adherent to its physical nature, we propose a new model simple and manageable. This model takes into account another random variable, representing the duration of the rainfall due to…
Stochastic Differential Equations
2020
Stochastic differential equations describe the time evolution of certain continuous n-dimensional Markov processes. In contrast with classical differential equations, in addition to the derivative of the function, there is a term that describes the random fluctuations that are coded as an Ito integral with respect to a Brownian motion. Depending on how seriously we take the concrete Brownian motion as the driving force of the noise, we speak of strong and weak solutions. In the first section, we develop the theory of strong solutions under Lipschitz conditions for the coefficients. In the second section, we develop the so-called (local) martingale problem as a method of establishing weak so…
Experimental Studies of Noise—Induced Phenomena in a Tunnel Diode
2007
Noise induced phenomena are investigated in a physical system based on a tunnel diode. The stochastic differential equation describing this physical system is analog to the Langevin equation of an overdamped Brownian particle diffusing in a nonlinear potential. This simple and versatile physical system allows a series of experiments testing and clarifying the role of the noise and of its correlation in the stochastic dynamics of bistable or metastable systems. Experimental investigations of stochastic resonance, resonant activation and noise enhanced stability are discussed.
Stochastic integro-differential and differential equations of non-linear systems excited by parametric Poisson pulses
1997
Abstract The connection between stochastic integro-differential equation and stochastic differential equation of non-linear systems driven by parametric Poisson delta correlated processes is presented. It is shown that the two different formulations are fully equivalent in the case of external excitation. In the case of parametric type excitation the two formulation are equivalent if the non-linear argument in the integral representation is related by means of a series to the corresponding non-linear parametric term in the stochastic differential equation. Differential rules for the two representations to find moment equations of every order of the response are also compared.