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We apply the topology of convergence on compact sets to define unpredictable functions [5, 6]. The topology is metrizable and easy for applications with integral operators. To demonstrate the effectiveness of the approach, the existence and…

Chaotic Dynamics · Physics 2016-11-17 Marat Akhmet , Mehmet Onur Fen

This paper is more an essay than a report. There is a gentle introduction to some issues in modeling, followed by the use of steepest descent methods to develop a model as contrasted to using such methods to solve one already in hand, as in…

Dynamical Systems · Mathematics 2015-04-07 Nikolas O. Aksamit , Don H. Tucker , James F. Tucker

Stochastic partial differential equations (SPDEs) represent a very active research field with numerous recent developments and breakthrough results. There are several well-established approaches and methods used to construct solutions for…

Probability · Mathematics 2019-08-27 Christian Kuehn , Alexandra Neamtu

Imposing some conditions on derivatives of the known functions, using the Fiber Contraction Theorem we prove the existence of $C^1$ solutions of a class of iterative functional equations which involves iterates of the unknown functions and…

Classical Analysis and ODEs · Mathematics 2022-10-13 Weiwei Shi , Xiao Tang

We present the general forms of piece-wise functions on partitioned domains satisfying an intrinsic $C^0$ or $C^1$ continuity across the sub-domain boundaries. These general forms are constructed based on a strategy stemming from the theory…

Numerical Analysis · Mathematics 2024-03-12 Jielin Yang , Suchuan Dong

Nonlinear differential equations (DEs) are used in a wide range of scientific problems to model complex dynamic systems. The differential equations often contain unknown parameters that are of scientific interest, which have to be estimated…

Computation · Statistics 2021-09-07 Shijia Wang , Shufei Ge , Renny Doig , Liangliang Wang

The random feature method (RFM) has demonstrated great potential in bridging traditional numerical methods and machine learning techniques for solving partial differential equations (PDEs). It retains the advantages of mesh-free approaches…

Numerical Analysis · Mathematics 2025-05-02 Mikhail Kuvakin , Zijian Mei , Jingrun Chen

A new method of solving third-order ordinary complex differential equations (OCDEs) by generalizing Prelle-Singer. The idea which is a procedure for finding the solution for second-order differential equations in the real domain. We have…

Mathematical Physics · Physics 2018-10-15 Ali Joohy , Mohammed S. Mechee , Ghassan A. Al-Juaifri

Differential equations where the graph of some derivative of a function is composed of a finite number of similarity transformations of the graph of the function itself are defined. We call these self-similar differential equations (SSDEs)…

Classical Analysis and ODEs · Mathematics 2024-09-17 Leon Q. Brin , Joe Fields

Discrete numerical methods with finite time-steps represent a practical technique to solve initial-value problems involving nonlinear differential equations. These methods seem particularly useful to the study of chaos since no analytical…

Chaotic Dynamics · Physics 2010-01-01 Lun-Shin Yao

New solution method for the systems of linear equations in commutative integral domains is proposed. Its complexity is the same that the complexity of the matrix multiplication.

Data Structures and Algorithms · Computer Science 2017-03-31 Gennadi Malaschonok

Nonlinear systems of partial differential equations (PDEs) may permit several distinct solutions. The typical current approach to finding distinct solutions is to start Newton's method with many different initial guesses, hoping to find…

Numerical Analysis · Mathematics 2015-07-03 Patrick E. Farrell , Ásgeir Birkisson , Simon W. Funke

We propose a methodology to address two analysis problems concerning complex systems, namely bounding state functionals of stochastic differential equations (SDEs) and verifying set avoidance of systems described by partial differential…

Optimization and Control · Mathematics 2016-03-30 Mohamadreza Ahmadi , Giorgio Valmorbida , Antonis Papachristodoulou

In differential equation discovery algorithms, numerical differentiation is usually a fixed preliminary step. Current methods improve robustness with data subsampling and sparsity but often ignore the variability from the differentiation…

Symbolic Computation · Computer Science 2025-12-16 Maria Khilchuk , Ilya Markov , Alexander Hvatov

We introduce a method for inferring an explicit PDE from a data sample generated by previously unseen dynamics, based on a learned context. The training phase integrates knowledge of the form of the equation with a differential scheme,…

Machine Learning · Computer Science 2024-06-10 Ori Linial , Orly Avner , Dotan Di Castro

In this paper, we introduce an iterative numerical method to solve systems of nonlinear equations. The third-order convergence of this method is analyzed. Several examples are given to illustrate the efficiency of the proposed method.

Dynamical Systems · Mathematics 2009-04-23 M. Eshaghi Gordji , A. Ebadian , M. B. Ghaemi , J. Shokri

Equations are about more than computing physical quantities or constructing formal models; they are also about understanding. The conceptual systems physicists use to think about nature are made from many different resources, formal and…

Physics Education · Physics 2018-04-06 Mark Eichenlaub , Edward F. Redish

The classical numerical methods play important roles in solving wave equation, e.g. finite difference time domain method. However, their computational domain are limited to flat space and the time. This paper deals with the description of…

Numerical Analysis · Mathematics 2010-01-22 Zheng Xie , Yujie Ma

There is a hidden intrigue in the title. CT is one of the most abstract mathematical disciplines, sometimes nicknamed "abstract nonsense". MDE is a recent trend in software development, industrially supported by standards, tools, and the…

Software Engineering · Computer Science 2012-09-10 Zinovy Diskin , Tom Maibaum

The solutions of fractional differential equations (FDEs) have a natural singularity at the initial point. The accuracy of their numerical solutions is lower than the accuracy of the numerical solutions of FDEs whose solutions are…

Numerical Analysis · Mathematics 2018-06-11 Yuri Dimitrov , Ivan Dimov , Venelin Todorov
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