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This note introduces a new notion of random dynamical system with inputs and outputs, and sketches a small-gain theorem for monotone systems which generalizes a similar theorem known for deterministic systems.

Systems and Control · Computer Science 2013-01-01 Michael Marcondes de Freitas , Eduardo D. Sontag

The paper deals with the variational principles for evaluation of the spectral radii of transfer and weighted shift operators associated with a dynamical system. These variational principles have been the matter of numerous investigations…

Dynamical Systems · Mathematics 2011-10-04 A. B. Antonevich , V. I. Bakhtin , A. V. Lebedev

The speed-gradient variational principle (SG-principle) is formulated and applied to thermodynamical systems. It is shown that Prigogine's principle of minimum entropy production and Onsager's symmetry relations can be interpreted in terms…

General Physics · Physics 2007-05-23 Alexander L. Fradkov

We extend the weak-strong uniqueness principle for mean-field game (MFG) systems to a broad class of second-order stationary and time-dependent problems. Under standard monotonicity, growth, and coercivity assumptions on the Hamiltonian,…

Analysis of PDEs · Mathematics 2026-04-02 Rita Ferreira , Diogo Gomes , Bashayer Majrashi

Nearly-elastic model systems with one or two degrees of freedom are considered: the system is undergoing a small loss of energy in each collision with the "wall". We show that instabilities in this purely deterministic system lead to…

Probability · Mathematics 2012-08-31 Mark Freidlin , Wenqing Hu

The combination of functional limit theorems with the pathwise analysis of deterministic and stochastic differential equations has proven to be a powerful approach to the analysis of fast-slow systems. In a multivariate setting, this…

Probability · Mathematics 2024-09-05 Maximilian Engel , Peter K. Friz , Tal Orenshtein

A method for designing variational principles for the dynamics of a possibly dissipative and non-conservatively forced chain of particles is demonstrated. Some qualitative features of the formulation are discussed.

Mathematical Physics · Physics 2024-04-05 Amit Acharya , Ambar N. Sengupta

We define variational properties for dynamical systems with subexponential complexity, and study these properties in certain specific examples. By computing the value of slow entropy directly, we show that some subshifts are not…

Dynamical Systems · Mathematics 2024-10-22 Minhua Cheng , Carlos Ospina , Kurt Vinhage , Yibo Zhai

For numerous parameter and state estimation problems, assimilating new data as they become available can help produce accurate and fast inference of unknown quantities. While most existing algorithms for solving those kind of ill-posed…

Numerical Analysis · Mathematics 2022-07-28 Neil K. Chada , Marco A. Iglesias , Shuai Lu , Frank Werner

A canonical formalism and constraint analysis for discrete systems subject to a variational action principle are devised. The formalism is equivalent to the covariant formulation, encompasses global and local discrete time evolution moves…

Mathematical Physics · Physics 2013-09-17 Bianca Dittrich , Philipp A Hoehn

We develop a new robust technique to deduce variance principles for non-integrable discrete systems. To illustrate this technique, we show the existence of a variational principle for graph homomorphisms from $\Z^m$ to a $d$-regular tree.…

Probability · Mathematics 2020-03-20 Georg Menz , Martin Tassy

We consider a sequence of additive functionals {\phi_n}, set on a sequence of Markov chains {X_n} that weakly converges to a Markov process X. We give sufficient condition for such a sequence to converge in distribution, formulated in terms…

Probability · Mathematics 2007-05-23 Yuri N. Kartashov , Alexey M. Kulik

The paper is concerned with the weak convergence of $n$-particle processes to deterministic stationary paths as $n\to\infty$. A Mosco type convergence of a class of bilinear forms is introduced. The Mosco type convergence of bilinear forms…

Probability · Mathematics 2013-03-14 Jörg-Uwe Löbus

For random dynamical systems, by summarizing the fundamental properties of Kifer's topological pressure we introduce the concept of random pressure functions, and define Ruelle's metric entropy for invariant measures. Employing the…

Dynamical Systems · Mathematics 2026-05-19 Rui Yang , Ercai Chen , Xiaoyao Zhou

We obtain strong invariance principles for normalized multiple iterated sums and integrals of the form $\bbS_N^{(\nu)}(t)=N^{-\nu/2}\sum_{0\leq k_1<...<k_\nu\leq Nt}\xi(k_1)\otimes\cdots\otimes\xi(k_\nu)$, $t\in[0,T]$ and…

Probability · Mathematics 2025-02-04 Yuri Kifer

Recently, Horv\'ath, Song, and Terlaky [\emph{A novel unified approach to invariance condition of dynamical system, submitted to Applied Mathematics and Computation}] proposed a novel unified approach to study, i.e., invariance conditions,…

Dynamical Systems · Mathematics 2016-09-06 Zoltán Horváth , Yunfei Song , Tamás Terlaky

The reduction of dynamical systems has a rich history, with many important applications related to stability, control and verification. Reduction of nonlinear systems is typically performed in an exact manner - as is the case with…

Optimization and Control · Mathematics 2007-07-26 Paulo Tabuada , Aaron D. Ames , Agung Julius , George J. Pappas

A moderate deviations principle for the law of a stochastic Burgers equation is proved via the weak convergence approach. In addition, some useful estimates toward a central limit theorem are established.

Probability · Mathematics 2020-01-17 Rachid Belfadli , Lahcen Boulanba , Mohamed Mellouk

We establish an invariance principle for a general class of stationary random fields indexed by $\mathbb Z^d$, under Hannan's condition generalized to $\mathbb Z^d$. To do so we first establish a uniform integrability result for stationary…

Probability · Mathematics 2014-07-17 Dalibor Volný , Yizao Wang

We focus on variational inference in dynamical systems where the discrete time transition function (or evolution rule) is modelled by a Gaussian process. The dominant approach so far has been to use a factorised posterior distribution,…

Machine Learning · Statistics 2018-12-17 Alessandro Davide Ialongo , Mark van der Wilk , James Hensman , Carl Edward Rasmussen
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