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Many simulations of stochastic processes require colored noises: I describe here an exact numerical method to simulate power-law noises: the method can be extended to more general colored noises, and is exact for all time steps, even when…

Computational Physics · Physics 2007-05-23 Edoardo Milotti

Starting from the developed generalized point process model of $1/f$ noise (B. Kaulakys et al, Phys. Rev. E 71 (2005) 051105; cond-mat/0504025) we derive the nonlinear stochastic differential equations for the signal exhibiting 1/f^{\beta}$…

Statistical Mechanics · Physics 2009-11-11 Bronislovas Kaulakys , Julius Ruseckas , Vygintas Gontis , Miglius Alaburda

This is an overview about natural sample spaces for differential equations driven by various noises. Appropriate sample spaces are needed in order to facilitate a random dynamical systems approach for stochastic differential equations. The…

Dynamical Systems · Mathematics 2009-12-02 Jinqiao Duan , Xingye Kan , Bjaorn Schmalfuss

A method for simulating power law noise in clocks and oscillators is presented based on modification of the spectrum of white phase noise, then Fourier transforming to the time domain. Symmetric real matrices are introduced whose…

Data Analysis, Statistics and Probability · Physics 2011-03-28 Neil Ashby

It is well known that a random multiplicative process with weak additive noise generates a power-law probability distribution. It has recently been recognized that this process exhibits another type of power law: the moment of the…

Statistical Mechanics · Physics 2007-05-23 Hiroya Nakao

Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients, and weakly dependent errors, are considered for observations over time, space or space--time. Consistency and asymptotic normality of…

Statistics Theory · Mathematics 2012-05-14 Peter M. Robinson

The generalized fractional Brownian motion is a Gaussian self-similar process whose increments are not necessarily stationary. It appears in applications as the scaling limit of a shot noise process with a power law shape function and…

Probability · Mathematics 2020-12-02 Tomoyuki Ichiba , Guodong Pang , Murad S. Taqqu

The two-variable Langevin equations, modeling the Brownian motion of a particle moving in a potential and leading to the Maxwell-Boltzmann distribution of the corresponding Fokker-Planck equation, are shown to give rise to types of…

Statistical Mechanics · Physics 2015-08-10 Jiulin Du

We consider a class of nonlinear stochastic differential equations, giving the power-law behavior of the power spectral density in any desirably wide range of frequency. Such equations were obtained starting from the point process models of…

Adaptation and Self-Organizing Systems · Physics 2015-05-18 J. Ruseckas , B. Kaulakys

Nonlinear stochastic differential equations generating signals with 1/f spectrum have been used so far to describe socio-economical systems. In this paper we consider the motion of a Brownian particle in an inhomogeneous environment such…

Statistical Mechanics · Physics 2015-06-23 Rytis Kazakevicius , Julius Ruseckas

Starting from the simple point process model of 1/f noise we derive a stochastic nonlinear differential equation for the signal exhibiting 1/f noise in any desirably wide range of frequency. A stochastic differential equation (the general…

Statistical Mechanics · Physics 2009-11-10 B. Kaulakys , J. Ruseckas

We present and analyze stochastic nonlinear differential equations generating signals with the power-law distributions of the signal intensity, 1/f^b noise, power-law autocorrelations and second order structural (height-height correlation)…

Adaptation and Self-Organizing Systems · Physics 2010-03-08 B. Kaulakys , M. Alaburda

There are several mathematical models yielding 1/f noise. For example, 1/f spectrum can be obtained from stochastic sequence of pulses having power-law distribution of pulse durations or from nonlinear stochastic differential equations. We…

Statistical Mechanics · Physics 2014-02-12 J. Ruseckas , B. Kaulakys

Procedural noise is a fundamental component of computer graphics pipelines, offering a flexible way to generate textures that exhibit "natural" random variation. Many different types of noise exist, each produced by a separate algorithm. In…

The modeling of intrinsic noise in pulsar timing residual data is of crucial importance for Gravitational Wave (GW) detection and pulsar timing (astro)physics in general. The noise budget in pulsars is a collection of several well studied…

Instrumentation and Methods for Astrophysics · Physics 2016-05-04 Justin Ellis , Neil Cornish

$1/f^\alpha$ noises are ubiquitous and affect many measurements. These noises are both a nuisance and a peculiarity of several physical systems; in dielectrics, glasses and networked liquids it is very common to study this noise to gather…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Edoardo Milotti

The ability of Gaussian noise to induce ordered states in dynamical systems is here presented in an overview of the main stochastic mechanisms able to generate spatial patterns. These mechanisms involve: (i) a deterministic local dynamics…

Statistical Mechanics · Physics 2012-05-14 Stefania Scarsoglio , Francesco Laio , Paolo D'Odorico , Luca Ridolfi

Stochastic processes with multiplicative noise have been studied independently in several different contexts over the past decades. We focus on the regime, found for a generic set of control parameters, in which stochastic processes with…

Statistical Mechanics · Physics 2015-06-25 D. Sornette

Stochastic phenomena in which the noise amplitude is proportional to the fluctuating variable itself, usually called {\it multiplicative noise}, appear ubiquitously in physics, biology, economy and social sciences. The properties of…

Condensed Matter · Physics 2007-05-23 Miguel A. Munoz

Machine learning, and in particular neural network models, have revolutionized fields such as image, text, and speech recognition. Today, many important real-world applications in these areas are driven by neural networks. There are also…

Probability · Mathematics 2019-11-12 Justin Sirignano , Konstantinos Spiliopoulos
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