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In this paper, we propose a computationally valid and theoretically justified methods, the likelihood ratio scan method (LRSM), for estimating multiple change-points in a piecewise stationary generalized conditional integer-valued…

Methodology · Statistics 2024-04-23 Danshu Sheng , Dehui Wang

We present a novel numerical method for solving the elliptic partial differential equation problem for the electrostatic potential with piecewise constant conductivity. We employ an integral equation approach for which we derive a system of…

Numerical Analysis · Mathematics 2022-06-01 Kyle Bower , Kirill Serkh , Spyros Alexakis , Adam R Stinchcombe

The differential transformation method (DTM) enables the easy construction of a power-series solution to a nonlinear differential equation. The exponentiation operation has not been specifically addressed in the DTM literature, and…

Classical Analysis and ODEs · Mathematics 2010-07-14 Hal Finkel

Recently, a novel method based on coding partitions [1]-[4] has been used to derive power series expansions to previously intractable problems. In this method the coefficients at $k$ are determined by summing the contributions made by each…

Combinatorics · Mathematics 2012-03-23 Victor Kowalenko

We provide algorithms computing power series solutions of a large class of differential or $q$-differential equations or systems. Their number of arithmetic operations grows linearly with the precision, up to logarithmic terms.

Symbolic Computation · Computer Science 2013-06-19 Alin Bostan , Muhammad F. I. Chowdhury , Romain Lebreton , Bruno Salvy , Éric Schost

In this contribution we consider localized, robust and efficient a-posteriori error estimation of the localized reduced basis multi-scale (LRBMS) method for parametric elliptic problems with possibly heterogeneous diffusion coefficient. The…

Numerical Analysis · Mathematics 2019-10-30 Mario Ohlberger , Felix Schindler

The Process Reward Model (PRM) plays a crucial role in mathematical reasoning tasks, requiring high-quality supervised process data. However, we observe that reasoning steps generated by Large Language Models (LLMs) often fail to exhibit…

Artificial Intelligence · Computer Science 2025-08-25 Yulan Hu , Sheng Ouyang , Jinman Zhao , Yong Liu

Spectral parameter power series (SPPS) representations for solutions of Sturm-Liouville equations proved to be an efficient practical tool for solving corresponding spectral and scattering problems. They are based on a computation of…

Classical Analysis and ODEs · Mathematics 2014-04-30 Vladislav V. Kravchenko , Sergii M. Torba

Hypercomplex signal processing (HSP) offers powerful tools for analyzing and processing multidimensional signals by explicitly exploiting inter-dimensional correlations through Clifford algebra. In recent years, hypercomplex formulations of…

Signal Processing · Electrical Eng. & Systems 2026-03-02 Kumar Vijay Mishra , Henry Arguello , Brian M. Sadler

The inversion of nabla Laplace transform, corresponding to a causal sequence, is considered. Two classical methods, i.e., residual calculation method and partial fraction method are developed to perform the inverse nabla Laplace transform.…

General Mathematics · Mathematics 2022-12-07 Yiheng Wei , YangQuan Chen , Yuquan Chen , Yong Wang

This paper deals the implementation of \emph{homotopy perturbation transform method} (HPTM) for numerical computation of initial valued autonomous system of time-fractional partial differential equations (TFPDEs) with proportional delay,…

Numerical Analysis · Mathematics 2018-02-19 Brajesh Kumar Singh , Pramod Kumar

A representation in the form of spectral parameter power series (SPPS) is given for a general solution of a one dimension Dirac system containing arbitrary matrix coefficient at the spectral parameter, \[ B \frac{dY}{dx} + P(x)Y = \lambda…

Classical Analysis and ODEs · Mathematics 2019-04-09 Nelson Gutiérrez Jiménez , Sergii M. Torba

This work introduces an ensemble parameter estimation framework that enables the Lumped Parameter Linear Superposition (LPLSP) method to generate reduced order thermal models from a single transient dataset. Unlike earlier implementations…

Numerical Analysis · Mathematics 2026-05-26 Neelakantan Padmanabhan

Machine learning has been successfully applied to various fields of scientific computing in recent years. In this work, we propose a sparse radial basis function neural network method to solve elliptic partial differential equations (PDEs)…

Numerical Analysis · Mathematics 2023-09-07 Zhiwen Wang , Minxin Chen , Jingrun Chen

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

Digital System Research has pioneered the mathematics and design for a new class of computing machine using residue numbers. Unlike prior art, the new breakthrough provides methods and apparatus for general purpose computation using several…

Other Computer Science · Computer Science 2015-12-04 Eric B. Olsen

Fractional calculus generalizes the derivative and antiderivative operations of differential and integral calculus from integer orders to the entire complex plane. Methods are presented for using this generalized calculus with Laplace…

Classical Analysis and ODEs · Mathematics 2007-05-23 F. S. Felber

A form of the Laplace transform is reviewed as a paradigm for an entire class of fractional functional transforms. Various of its properties are discussed. Such transformations should be useful in application to differential/integral…

Data Analysis, Statistics and Probability · Physics 2018-04-30 R. A. Treumann , W. Baumjohann

Meshless methods are often used in numerical simulations of systems of partial differential equations (PDEs), particularly those which involve complex geometries or free surfaces. Here we present a novel compact scheme based on the local…

Numerical Analysis · Mathematics 2026-03-13 Henry M. Broadley , Steven J. Lind , Jack R. C. King

We present a novel technique for constructing differentiable order-type operations, including soft ranking, soft top-k selection, and soft permutations. Our approach leverages an efficient closed-form formula for the inverse of the function…

Artificial Intelligence · Computer Science 2025-09-04 Łukasz Struski , Michał B. Bednarczyk , Igor T. Podolak , Jacek Tabor