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Particle filters are applicable to a wide range of nonlinear, non-Gaussian state-space models and have already been applied to a variety of problems. However, there is a problem in the calculation of smoothed distributions, where particles…

Computation · Statistics 2024-05-16 G. Kitagawa

This work develops Monte Carlo Euler adaptive time stepping methods for the weak approximation problem of jump diffusion driven stochastic differential equations. The main result is the derivation of a new expansion for the omputational…

Numerical Analysis · Mathematics 2007-05-23 E. Mordecki , A. Szepessy , R. Tempone , G. E. Zouraris

Time integration methods for solving initial value problems are an important component of many scientific and engineering simulations. Implicit time integrators are desirable for their stability properties, significantly relaxing…

Numerical Analysis · Mathematics 2020-11-24 Ross Glandon , Mahesh Narayanamurthi , Adrian Sandu

A new class of iterated linearization-based nonlinear filters, dubbed dynamically iterated filters, is presented. Contrary to regular iterated filters such as the iterated extended Kalman filter (IEKF), iterated unscented Kalman filter…

Signal Processing · Electrical Eng. & Systems 2023-09-15 Anton Kullberg , Isaac Skog , Gustaf Hendeby

Within this paper, we introduce and analyze a novel time stepping scheme for linear poroelasticity. In each time frame, we iteratively solve the flow and mechanics equations with an additional damping step for the pressure variable.…

Numerical Analysis · Mathematics 2025-03-12 R. Altmann , M. Deiml

Inference for partially observed Markov process models has been a longstanding methodological challenge with many scientific and engineering applications. Iterated filtering algorithms maximize the likelihood function for partially observed…

Statistics Theory · Mathematics 2012-11-26 Edward L. Ionides , Anindya Bhadra , Yves Atchadé , Aaron King

Bayesian filtering approximates the true underlying behavior of a time-varying system by inverting an explicit generative model to convert noisy measurements into state estimates. This process typically requires either storage, inversion,…

Machine Learning · Computer Science 2023-11-20 Gianluca M. Bencomo , Jake C. Snell , Thomas L. Griffiths

In this note we propose and analyze novel implicit-explicit methods based on second order strong stability preserving multistep time discretizations. Several schemes are developed, and a linear stability analysis is performed to study their…

Numerical Analysis · Mathematics 2025-10-20 Thor Gjesdal

We introduce a class of unconditionally energy stable, high order accurate schemes for gradient flows in a very general setting. The new schemes are a high order analogue of the minimizing movements approach for generating a time discrete…

Numerical Analysis · Mathematics 2020-02-11 Alexander Zaitzeff , Selim Esedoglu , Krishna Garikipati

The dynamic environment in the real world calls for the adaptive techniques for information filtering, namely to provide real-time responses to the changes of system data. Where many incremental algorithms are designed for this purpose,…

Information Retrieval · Computer Science 2009-11-26 Ci-Hang Jin , Jian-Guo Liu , Yi-Cheng Zhang , Tao Zhou

In this paper, we delve into the concept of interpretable image enhancement, a technique that enhances image quality by adjusting filter parameters with easily understandable names such as "Exposure" and "Contrast". Unlike using predefined…

Computer Vision and Pattern Recognition · Computer Science 2024-08-21 Satoshi Kosugi

There are many methods developed to mitigate transients induced when abruptly changing dynamic algorithms such as those found in digital filters or controllers. These "bumpless transfer" methods have a computational burden to them and take…

Systems and Control · Computer Science 2018-08-24 Michael Giardino , Wayne Maxwell , Bonnie Ferri , Aldo Ferri

Sequential Monte Carlo methods have been a major breakthrough in the field of numerical signal processing for stochastic dynamical state-space systems with partial and noisy observations. However, these methods still present certain…

Applications · Statistics 2023-12-14 Samuel Nyobe , Fabien Campillo , Serge Moto , Vivien Rossi

This work deals with the problem of choosing a time step for the numerical solution of boundary value problems for parabolic equations. The problem solution is derived using the fully implicit scheme, whereas a time step is selected via…

Numerical Analysis · Computer Science 2013-11-13 Petr N. Vabishchevich

Real life signals are in general non--stationary and non--linear. The development of methods able to extract their hidden features in a fast and reliable way is of high importance in many research fields. In this work we tackle the problem…

Numerical Analysis · Mathematics 2018-10-26 Antonio Cicone , Haomin Zhou

We introduce a semi-explicit time-stepping scheme of second order for linear poroelasticity satisfying a weak coupling condition. Here, semi-explicit means that the system, which needs to be solved in each step, decouples and hence improves…

Numerical Analysis · Mathematics 2023-11-08 R. Altmann , R. Maier , B. Unger

This paper presents a joint optimisation framework for optimal estimation and stochastic optimal control with imperfect information. It provides a estimation and control scheme that can be decomposed into a classical optimal estimation step…

Optimization and Control · Mathematics 2023-03-27 Emilien Flayac , Karim Dahia , Bruno Hérissé , Frédéric Jean

In this paper we continue our work on adaptive timestep control for weakly non- stationary problems. The core of the method is a space-time splitting of adjoint error representations for target functionals due to S\"uli and Hartmann. The…

Numerical Analysis · Mathematics 2014-06-19 Christina Steiner , Siegfried Müller , Sebastian Noelle

In this paper, we extend the implicit-explicit (IMEX) methods of Peer type recently developed in [Lang, Hundsdorfer, J. Comp. Phys., 337:203--215, 2017] to a broader class of two-step methods that allow the construction of super-convergent…

Numerical Analysis · Mathematics 2018-06-08 Moritz Schneider , Jens Lang , Willem Hundsdorfer

Efficient high order numerical methods for evolving the solution of an ordinary differential equation are widely used. The popular Runge--Kutta methods, linear multi-step methods, and more broadly general linear methods, all have a global…

Numerical Analysis · Mathematics 2020-03-16 Adi Ditkowski , Sigal Gottlieb , Zachary J. Grant