Results 211 to 220 of about 29,606 (263)

Dynamic behavior of a stochastic epidemic model for skin sores: theoretical and computational perspectives. [PDF]

Sci Rep
Raza A, Lampart M, Rocha EM, Baleanu D, Taha HH, Fadhal E.   +5 more
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Modeling of gene regulatory networks: an annotated glossary. [PDF]

Trends Plant Sci
Singh Yadav A, Russell NJ, Hernández AI, Petlewski AR, Johnson AR, Grinage AD, Banuna B, Guan CJ, Mahood EH, Younkin GC, Thomas HR, Phillips HR, Harline K, Flasco M, Miller MB, Scinto-Madonich NJ, Szeluga NM, Mendoza PN, Formosa-Jordan P, Roeder AHK.   +19 more
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Dynamical behavior of analytic solutions of the generalized derivative nonlinear Schrödinger equation under stochastic perturbations in fiber communication systems. [PDF]

Sci Rep
Murad MAS, Abdullah AR, Mustafa MA, Hussain E.   +3 more
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MorphoGrad: A MATLAB toolbox for simulating steady-state morphogen gradients under cell-to-cell variability. [PDF]

STAR Protoc
Adelmann JA, Vetter R, Iber D.
europepmc   +1 more source

Virtual cell: Current perspectives and future prospects. [PDF]

J Int Med Res
Li J, Zhang H, Zhang W, Li N, Zhao F, Shen G.   +5 more
europepmc   +1 more source

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Contraction of stochastic differential equations

Communications in Nonlinear Science and Numerical Simulation, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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On solving stochastic differential equations

Monte Carlo Methods and Applications, 2019
Abstract This paper proposes a new approach to solving Ito stochastic differential equations. It is based on the well-known Monte Carlo methods for solving integral equations (Neumann–Ulam scheme, Markov chain Monte Carlo). The estimates of the solution for a wide class of equations do not have a bias, which distinguishes them from ...
Sergej M. Ermakov, Anna A. Pogosian
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Stochastic differential equations

Physics Reports, 1976
Abstract In chapter I stochastic differential equations are defined and classified, and their occurrence in physics is reviewed. In chapter II it is shown for linear equation show a differential equation for the averaged solution is obtained by expanding in ατ c , where α measures the size of the fluctuations and τ c their autocorrelation time. This
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Stochastic differential equations

2011
In this chapter we present some basic results on stochastic differential equations, hereafter shortened to SDEs, and we examine the connection to the theory of parabolic partial differential equations.
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