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We propose novel parameter estimation algorithms for a class of dynamical systems with nonlinear parametrization. The class is initially restricted to smooth monotonic functions with respect to a linear functional of the parameters. We show…

Dynamical Systems · Mathematics 2007-05-23 Ivan Tyukin , Danil Prokhorov , Cees van Leeuwen

A generic non-integrable (unitary) out-of-equilibrium quantum process, when interrogated across many times, is shown to yield the same statistics as an (non-unitary) equilibrated process. In particular, using the tools of quantum stochastic…

Quantum Physics · Physics 2023-07-18 Neil Dowling , Pedro Figueroa-Romero , Felix A. Pollock , Philipp Strasberg , Kavan Modi

The asynchronous systems are the non-deterministic models of the asynchronous circuits from the digital electrical engineering. In the autonomous version, such a system is a set of functions x:R{\to}{0,1}^{n} called states (R is the time…

Other Computer Science · Computer Science 2013-07-23 Serban E. Vlad

We extend the notions of conditioned and controlled invariant spaces to linear dynamical systems over the max-plus or tropical semiring. We establish a duality theorem relating both notions, which we use to construct dynamic observers.…

Optimization and Control · Mathematics 2010-12-20 Michael Di Loreto , Stephane Gaubert , Ricardo D. Katz , Jean-Jacques Loiseau

A fundamental challenge is to understand nonequilibrium statistical mechanics starting from microscopic chaos in the equations of motion of a many-particle system. In this review we summarize recent theoretical advances along these lines.…

Chaotic Dynamics · Physics 2010-01-04 R. Klages

In this paper we define a class of polynomial functors suited for constructing coalgebras representing processes in which uncertainty plays an important role. In these polynomial functors we include upper and lower probability measures,…

Logic in Computer Science · Computer Science 2024-04-02 Andrés Gallardo , Ignacio Viglizzo

Linear dynamical systems are the foundational statistical model upon which control theory is built. Both the celebrated Kalman filter and the linear quadratic regulator require knowledge of the system dynamics to provide analytic…

Optimization and Control · Mathematics 2023-01-24 Ainesh Bakshi , Allen Liu , Ankur Moitra , Morris Yau

Closed quantum systems obey the Schroedinger equation whereas nonequilibrium behavior of many of systems is routinely described in terms of classical, Markovian stochastic processes. Evidently, there are fundamental differences between…

Quantum Physics · Physics 2016-02-29 Daniel Schmidtke , Jochen Gemmer

The suggestion of writing, for some problems, nonlinear state equations not as dx/dt = F(x,u,t), but as dx/dt = [A(t,x)]x + [B(t,x)]u(t), which is more "constructive", is considered supported by arguments related to: the axiomatization of…

Exactly Solvable and Integrable Systems · Physics 2008-10-24 Emanuel Gluskin

We investigate the correspondence between a non-equilibrium ensemble defined via the distribution of phase-space paths of a Hamiltonian system, and a system driven into a steady-state by non-equilibrium boundary conditions. To discover…

Statistical Mechanics · Physics 2014-01-27 Milos Knezevic , R. M. L. Evans

We study the ordering dynamics of nonlinear voter models with multiple states, also providing a discussion of the two-state model. The rate with which an individual adopts an opinion scales as the $q$-th power of the number of the…

Physics and Society · Physics 2023-11-01 Lucía Soledad Ramirez , Federico Vazquez , Maxi San Miguel , Tobias Galla

The strong convergence of the semi-implicit Euler-Maruyama (EM) method for stochastic differential equations with non-linear coefficients driven by a class of L\'evy processes is investigated. The dependence of the convergence order of the…

Numerical Analysis · Mathematics 2023-11-21 Xiaotong Li , Wei Liu , Hongjiong Tian

A labelled Markov decision process is a labelled Markov chain with nondeterminism, i.e., together with a strategy a labelled MDP induces a labelled Markov chain. The model is related to interval Markov chains. Motivated by applications of…

Formal Languages and Automata Theory · Computer Science 2020-09-25 Stefan Kiefer , Qiyi Tang

The simulation of complex stochastic network dynamics arising, for instance, from models of coupled biomolecular processes remains computationally challenging. Often, the necessity to scan a models' dynamics over a large parameter space…

Quantitative Methods · Quantitative Biology 2013-03-14 Tiago Ramalho , Marco Selig , Ulrich Gerland , Torsten A. Enßlin

The topic of statistical inference for dynamical systems has been studied extensively across several fields. In this survey we focus on the problem of parameter estimation for non-linear dynamical systems. Our objective is to place results…

Statistics Theory · Mathematics 2012-06-19 Kevin McGoff , Sayan Mukherjee , Natesh S. Pillai

A formulation of Langevin dynamics for discrete systems is derived as a class of generic stochastic processes. The dynamics simplify for a two-state system and suggest a network architecture which is implemented by the Langevin machine. The…

Neural and Evolutionary Computing · Computer Science 2021-04-08 Lukas Kades , Jan M. Pawlowski

Consider the multicolored urn model where, after every draw, balls of the different colors are added to the urn in a proportion determined by a given stochastic replacement matrix. We consider some special replacement matrices which are not…

Probability · Mathematics 2009-02-09 Arup Bose , Amites Dasgupta , Krishanu Maulik

The two-dimensional cell-sorting problem is found to be mathematically equivalent to the one-dimensional random walk problem with pair creations and annihilations, i.e. the adhesion probabilities in the cell-sorting model relate…

Cell Behavior · Quantitative Biology 2011-07-01 Kazuhiko Minami

Obtaining dynamics models is essential for robotics to achieve accurate model-based controllers and simulators for planning. The dynamics models are typically obtained using model specification of the manufacturer or simple numerical…

Robotics · Computer Science 2021-10-26 Michael Lutter , Johannes Silberbauer , Joe Watson , Jan Peters

This work presents the concept of kernel mean embedding and kernel probabilistic programming in the context of stochastic systems. We propose formulations to represent, compare, and propagate uncertainties for fairly general stochastic…

Machine Learning · Statistics 2020-05-05 Jia-Jie Zhu , Krikamol Muandet , Moritz Diehl , Bernhard Schölkopf
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