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In this paper it is reconsidered the prediction problem in time series framework by using a new non-parametric approach. Through this reconsideration, the prediction is obtained by a weighted sum of past observed data. These weights are…

Machine Learning · Statistics 2021-01-27 Pedro Cadahía , Jose Manuel Bravo Caro

This paper is devoted to provide a theoretical underpinning for ensemble forecasting with rapid fluctuations in body forcing and in boundary conditions. Ensemble averaging principles are proved under suitable `mixing' conditions on random…

Probability · Mathematics 2012-07-26 Wei Wang , Jian Ren , Jinqiao Duan , Guowei He

In many practical applications, signals and environments are time- varying, which makes fixed filters unreliable. Adaptive filtering, on the other hand, updates in real time to suppress noise, track nonstationary signals, and identify…

General Mathematics · Mathematics 2026-03-12 Keshav Raj Acharya , Pitambar Acharya

We consider a dynamic method, based on synchronization and adaptive control, to estimate unknown parameters of a nonlinear dynamical system from a given scalar chaotic time series. We present an important extension of the method when time…

Chaotic Dynamics · Physics 2009-10-31 Anil Maybhate , R. E. Amritkar

Hierarchical time series are common in several applied fields. The forecasts for these time series are required to be coherent, that is, to satisfy the constraints given by the hierarchy. The most popular technique to enforce coherence is…

Machine Learning · Statistics 2023-10-13 Lorenzo Zambon , Dario Azzimonti , Giorgio Corani

This paper proposes a new methodology in linear time-periodic (LTP) system identification. In contrast to previous methods that totally separate dynamics at different tag times for identification, the method focuses on imposing appropriate…

Systems and Control · Electrical Eng. & Systems 2021-11-10 Mingzhou Yin , Andrea Iannelli , Mohammad Khosravi , Anilkumar Parsi , Roy S. Smith

Nonlinear systems are capable of displaying complex behavior even if this is the result of a small number of interacting time scales. A widely studied case is when complex dynamics emerges out of a nonlinear system being forced by a simple…

Quantitative Methods · Quantitative Biology 2015-06-01 Leandro M. Alonso

We derive an efficient stochastic algorithm for inverse problems that present an unknown linear forcing term and a set of nonlinear parameters to be recovered. It is assumed that the data is noisy and that the linear part of the problem is…

Numerical Analysis · Mathematics 2019-09-17 Darko Volkov

This work concerns the nonlinear filtering problem of multiscale McKean-Vlasov stochastic systems where the whole systems depend on distributions of fast components. First of all, we prove that the slow component of the original system…

Probability · Mathematics 2023-11-27 Huijie Qiao , Wanlin Wei

The averaging theory has been extensively employed for studying periodic solutions of smooth and nonsmooth differential systems. Here, we extend the averaging theory for studying periodic solutions a class of regularly perturbed…

Dynamical Systems · Mathematics 2021-10-08 Jaume Llibre , Douglas Duarte Novaes , Iris de Oliveira Zeli

Linear Hamiltonian systems with time-dependent coefficients are of importance to nonlinear Hamiltonian systems, accelerator physics, plasma physics, and quantum physics. It is shown that the solution map of a linear Hamiltonian system with…

Mathematical Physics · Physics 2024-12-12 Hong Qin

In this paper, based on real-time nonlinear receding horizon control methodology, a novel approach is developed for parameter estimation of time invariant and time varying nonlinear dynamical systems in chaotic environments. Here, the…

Optimization and Control · Mathematics 2016-11-21 Fei Sun , Kamran Turkoglu

Time series forecasting typically needs to address non-stationary data with evolving trend and seasonal patterns. To address the non-stationarity, reversible instance normalization has been recently proposed to alleviate impacts from the…

Machine Learning · Computer Science 2024-10-01 Weiwei Ye , Songgaojun Deng , Qiaosha Zou , Ning Gui

We focus here on a class of fourth-order parabolic equations that can be written as a system of second-order equations by introducing an auxiliary variable. We design a novel second-order fully discrete mixed finite element method to…

Numerical Analysis · Mathematics 2020-08-28 Sana Keita , Abdelaziz Beljadid , Yves Bourgault

The problem of inferring pair-wise and higher-order interactions in complex systems involving large numbers of interacting variables, from observational data, is fundamental to many fields. Known to the statistical physics community as the…

Methodology · Statistics 2021-01-01 Sjoerd Viktor Beentjes , Ava Khamseh

We describe a novel algorithm for solving general parametric (nonlinear) eigenvalue problems. Our method has two steps: first, high-accuracy solutions of non-parametric versions of the problem are gathered at some values of the parameters;…

Numerical Analysis · Mathematics 2024-10-14 Davide Pradovera , Alessandro Borghi

We describe a proof-of-concept development and application of a phase averaging technique to the nonlinear rotating shallow water equations on the sphere, discretised using compatible finite element methods. Phase averaging consists of…

Numerical Analysis · Mathematics 2023-05-15 Hiroe Yamazaki , Colin J Cotter , Beth Wingate

In the present paper we derive Liouville type results and existence of periodic solutions for $\chi^{(2)}$ type systems with non-homogeneous nonlinearities. Moreover, we prove both universal bounds as well as singularity and decay estimates…

Analysis of PDEs · Mathematics 2023-06-27 Aleks Jevnikar , Jun Wang , Wen Yang

In this paper, non-Hamiltonian systems with holonomic constraints are treated by a generalization of Dirac's formalism. Non-Hamiltonian phase space flows can be described by generalized antisymmetric brackets or by general Liouville…

Statistical Mechanics · Physics 2009-11-11 Alessandro Sergi

We describe a convergence acceleration technique for unconstrained optimization problems. Our scheme computes estimates of the optimum from a nonlinear average of the iterates produced by any optimization method. The weights in this average…

Optimization and Control · Mathematics 2019-04-16 Damien Scieur , Alexandre d'Aspremont , Francis Bach