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A parameter estimation method is devised for a slow-fast stochastic dynamical system, where often only the slow component is observable. By using the observations only on the slow component, the system parameters are estimated by working on…

Dynamical Systems · Mathematics 2013-03-20 Jian Ren , Jinqiao Duan

Many real-world systems modeled using partial differential equations (PDEs) involve unknown parameters that must be estimated from limited, noisy system observations. While typically assumed to be constants, some of these unobserved…

Methodology · Statistics 2025-08-19 Andrea Arnold

This paper considers the problem of testing whether there exists a solution satisfying certain non-negativity constraints to a linear system of equations. Importantly and in contrast to some prior work, we allow all parameters in the system…

Transferring information from observations of a dynamical system to estimate the fixed parameters and unobserved states of a system model can be formulated as the evaluation of a discrete time path integral in model state space. The…

Chaotic Dynamics · Physics 2015-05-14 John C. Quinn , Henry D. I. Abarbanel

In this paper we study the problem of inferring the initial conditions of a dynamical system under incomplete information. Studying several model systems, we infer the latent microstates that best reproduce an observed time series when the…

Dynamical Systems · Mathematics 2022-04-04 Blas Kolic , Juan Sabuco , J. Doyne Farmer

This paper describes a method for the online state estimation of systems described by a general class of linear noncausal time-varying difference descriptor equations subject to uncertainties. The method is based on the notions of a linear…

Optimization and Control · Mathematics 2007-11-09 Serhiy M. Zhuk

In this paper, we propose a class of efficient, accurate, and general methods for solving state-estimation problems with equality and inequality constraints. The methods are based on recent developments in variable splitting and partially…

Optimization and Control · Mathematics 2020-12-02 Rui Gao , Filip Tronarp , Simo Särkkä

Literatures in state space models focus on parametric inference and prediction, which fail if the state space model is not fully specified and the maximum likelihood estimation does not work. In this paper, we assume the state transition…

Statistics Theory · Mathematics 2020-12-15 Yunyi Zhang , Tingting Wang , Dimitris N. Politis

In this paper, we focus on activating only a few sensors, among many available, to estimate the state of a stochastic process of interest. This problem is important in applications such as target tracking and simultaneous localization and…

Systems and Control · Computer Science 2016-09-28 Vasileios Tzoumas , Nikolay A. Atanasov , Ali Jadbabaie , George J. Pappas

The problem of effective use of Phasor Measurement Units (PMUs) to enhance power systems awareness and security is a topic of key interest. The central question to solve is how to use this new measurements to reconstruct the state of the…

Systems and Control · Electrical Eng. & Systems 2020-04-16 Alexey Bobtsov , Romeo Ortega , Nikolay Nikolaev , Johannes Schiffer , M. Nicolai L. Lorenz-Meyer

Set-based state estimation computes sets of states consistent with a system model given bounded sets of disturbances and noise. Bounding the set of states is crucial for safety-critical applications so that one can ensure that all…

Systems and Control · Electrical Eng. & Systems 2026-02-04 Nico Holzinger , Matthias Althoff

This article investigates stochastic epidemic models with partial information and addresses the estimation of current values of not directly observable states. The latter is also called nowcasting and related to the so-called "dark figure"…

Populations and Evolution · Quantitative Biology 2025-06-03 Florent Ouabo Kamkumo , Ibrahim Mbouandi Njiasse , Ralf Wunderlich

We introduce a simple method to estimate the system parameters in continuous dynamical systems from the time series. In this method, we construct a modified system by introducing some constants (controlling constants) into the given…

Chaotic Dynamics · Physics 2009-11-10 P. Palaniyandi , M. Lakshmanan

Complex systems are sometimes subject to non Gaussian alpha stable Levy fluctuations. A new method is devised to estimate this uncertain parameter and other system parameters, using observations on either mean exit time or escape…

Dynamical Systems · Mathematics 2013-06-04 Ting Gao , Jinqiao Duan

A new approach to design of nonlinear observers (state estimators) is proposed. The main idea is to (i) construct a convex set of dynamical systems which are contracting observers for a particular system, and (ii) optimize over this set for…

Systems and Control · Computer Science 2017-11-23 Ian R. Manchester

State estimation plays a key role in the transition from the passive to the active operation of distribution systems, as it allows to monitor these networks and, successively, to perform control actions. However, designing state estimators…

Systems and Control · Electrical Eng. & Systems 2020-11-25 Marta Vanin , Tom Van Acker , Reinhilde D'hulst , Dirk Van Hertem

A possible approach to description of the non equilibrium system has been proposed. Based on the Fokker-Plank equation in term of energy for non equilibrium distribution function of macroscopical system was obtained the stationary solution…

Statistical Mechanics · Physics 2008-08-08 Bohdan Lev

In this paper, the problem of partial stabilization of nonlinear systems along a given trajectory is considered. This problem is treated within the framework of stability of a family of sets. Sufficient conditions for the asymptotic…

Optimization and Control · Mathematics 2024-07-30 Victoria Grushkovskaya , Iryna Vasylieva , Alexander Zuyev

System state estimation constitutes a key problem in several applications involving multi-agent system architectures. This rests upon the estimation of the state of each agent in the group, which is supposed to access only relative…

Systems and Control · Electrical Eng. & Systems 2021-07-16 Marco Fabris , Giulia Michieletto , Angelo Cenedese

Information in the time distribution of points in a state space reconstructed from observed data yields a test for ``nonstationarity''. Framed in terms of a statistical hypothesis test, this numerical algorithm can discern whether some…

chao-dyn · Physics 2008-02-03 Matthew B. Kennel