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A computation-oriented representation of uncertain kinetic systems is introduced and analysed in this paper. It is assumed that the monomial coefficients of the ODEs belong to a polytopic set, which defines a set of dynamical systems for an…

Dynamical Systems · Mathematics 2018-05-23 Bernadett Ács , Gergely Szlobodnyik , Gábor Szederkényi

A classical question of propositional logic is one of the shortest proof of a tautology. A related fundamental problem is to determine the relative efficiency of standard proof systems, where the relative complexity is measured using the…

Logic in Computer Science · Computer Science 2017-03-21 Olga Tveretina

A stochastic process with self-interaction as a model of quantum field theory is studied. We consider an Ornstein-Uhlenbeck stochastic process x(t) with interaction of the form x^{(\alpha)}(t)^4, where $\alpha$ indicates the fractional…

Quantum Physics · Physics 2017-08-23 Yaroslav Volovich

We derive a generalization of the Wiener-Khinchin theorem for nonstationary processes by introducing a time-dependent spectral density that is related to the time-averaged power. We use the nonstationary theorem to investigate aging…

Statistical Mechanics · Physics 2015-09-02 Andreas Dechant , Eric Lutz

Likelihood-based inference in stochastic non-linear dynamical systems, such as those found in chemical reaction networks and biological clock systems, is inherently complex and has largely been limited to small and unrealistically simple…

Computation · Statistics 2024-07-08 Ben Swallow , David A. Rand , Giorgos Minas

The body of work presented here revolves around the investigation of the existence and nature of extra-solar planetary systems. The fitting of stellar radial velocity time series data is attempted by constructing a model to quantify the…

Astrophysics · Physics 2017-02-13 Gur Windmiller , Don Short , Jerome Orosz

We present a multifractal formalism for measures on infinite dimensional metric spaces, in terms of scales instead of dimensions in the classical multifractal analysis. We prove a multifractal formalism with a suitable scaling, called…

Probability · Mathematics 2026-02-16 Aihua Fan , Mathieu Helfter

A central tool in the study of systems of linear equations with integer coefficients is the Generalised von Neumann Theorem of Green and Tao. This theorem reduces the task of counting the weighted solutions of these equations to that of…

Number Theory · Mathematics 2020-08-05 Aled Walker

An adaptive state observer is proposed for a class of overparametrized uncertain linear time-invariant systems without restrictive requirement of their representation in the observer canonical form. It evolves the method of generalized…

Systems and Control · Electrical Eng. & Systems 2023-01-19 Anton Glushchenko , Konstantin Lastochkin

Complex Ornstein-Uhlenbeck (OU) processes have various applications in statistical modelling. They play role e.g. in the description of the motion of a charged test particle in a constant magnetic field or in the study of rotating waves in…

Statistics Theory · Mathematics 2018-08-13 Sándor Baran , Csilla Szák-Kocsis , Milan Stehlík

In \cite{BNT}, a framework to prove almost sure central limit theorems for sequences $(G_n)$ belonging to the Wiener space was developed, with a particular emphasis of the case where $G_n$ takes the form of a multiple Wiener-It\^o integral…

Probability · Mathematics 2019-01-21 Ehsan Azmoodeh , Ivan Nourdin

A system of nonlinear ordinary differential equations with forcing function is developed to model evolution processes in complex systems. In this system R, C, and P are the resource, consumption, and production functions correspondingly. F…

Atmospheric and Oceanic Physics · Physics 2017-11-01 Lev A Maslov

Some Wiener--Hopf determinants on [0,s] are calculated explicitly for all s>0. Their symbols are zero on an interval and they are related to the determinant with the sine-kernel appearing in the random matrix theory. The determinants are…

Functional Analysis · Mathematics 2007-05-23 I. V. Krasovsky

A new Bayesian approach to linear system identification has been proposed in a series of recent papers. The main idea is to frame linear system identification as predictor estimation in an infinite dimensional space, with the aid of…

Machine Learning · Statistics 2015-07-03 Diego Romeres , Gianluigi Pillonetto , Alessandro Chiuso

The problem of state estimation for a system of coupled hyperbolic PDEs and ODEs with Lipschitz nonlinearities with boundary measurements is considered. An infinite dimensional observer with a linear boundary injection term is used to solve…

Systems and Control · Electrical Eng. & Systems 2021-01-19 Francesco Ferrante , Andrea Cristofaro

We obtain exact, simple and very compact expressions for the linearization coefficients of the products of orthogonal polynomials; both the conventional Clebsch-Gordan-type and the modified version. The expressions are general depending…

Classical Analysis and ODEs · Mathematics 2023-06-09 A. D. Alhaidari

In this paper, we extend the method proposed by Cochelin and Vergez [A high order purely frequency-based harmonic balance formulation for continuation of periodic solutions, Journal of Sound and Vibration, 324 (2009) 243-262] to the case of…

Classical Physics · Physics 2012-11-29 Sami Karkar , Bruno Cochelin , Christophe Vergez

The goal of this paper is to compute the generating series of a closed-loop system when the plant is described in terms of a Chen-Fliess series and an additive static output feedback is applied. The first step is to consider the so called…

Systems and Control · Electrical Eng. & Systems 2021-10-20 G. S. Venkatesh , W. Steven Gray

We propose an extended method for experiment design in nonlinear state space models. The proposed input design technique optimizes a scalar cost function of the information matrix, by computing the optimal stationary probability mass…

Optimization and Control · Mathematics 2015-09-03 Patricio E. Valenzuela , Johan Dahlin , Cristian R. Rojas , Thomas B. Schön

Stochastic processes are often represented through orthonormal series expansions, a framework originating in the classical works of Lo\`eve and Karhunen and widely used for simulation and numerical approximation. While truncation error in…

Statistics Theory · Mathematics 2026-03-30 Oleksandr Mokliachuk
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