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The Adomian decomposition method is a semi-analytical method for solving ordinary and partial nonlinear differential equations. The aim of this paper is to apply Adomian decomposition method to obtain approximate solutions of nonlinear…

Numerical Analysis · Mathematics 2017-12-27 Iqra Javed , Ashfaq Ahmad , Muzammil Hussain , S. Iqbal

In this paper, we explore how numerical calculations can be accelerated by implementing several numerical methods of fractional-order systems using parallel computing techniques. We investigate the feasibility of parallel computing…

Dynamical Systems · Mathematics 2016-11-29 A. Baban , C. Bonchiş , A. Fikl , F. Roşu

This paper introduces a new method of partitioning the solution space of a multi-objective optimisation problem for parallel processing, called Efficient Projection Partitioning. This method projects solutions down into a single dimension,…

Optimization and Control · Mathematics 2017-11-23 William Pettersson , Melih Ozlen

In this study the general formula for differential and integral operations of fractional calculus via fractal operators by the method of cumulative diminution and cumulative growth is obtained. The under lying mechanism in the success of…

Statistical Mechanics · Physics 2016-08-31 Fevzi Buyukkilic , Zahide Ok Bayrakdar , Dogan Demirhan

New numerical algorithms based on rational functions are introduced that can solve certain Laplace and Helmholtz problems on two-dimensional domains with corners faster and more accurately than the standard methods of finite elements and…

Numerical Analysis · Mathematics 2022-10-12 Abinand Gopal , Lloyd N. Trefethen

Nonnegative matrix factorization (NMF) is a powerful technique for dimension reduction, extracting latent factors and learning part-based representation. For large datasets, NMF performance depends on some major issues: fast algorithms,…

Optimization and Control · Mathematics 2015-07-01 Duy-Khuong Nguyen , Tu-Bao Ho

We present a generic partition refinement algorithm that quotients coalgebraic systems by behavioural equivalence, an important task in system analysis and verification. Coalgebraic generality allows us to cover not only classical…

Data Structures and Algorithms · Computer Science 2023-06-22 Thorsten Wißmann , Ulrich Dorsch , Stefan Milius , Lutz Schröder

We present efficient algorithms to build data structures and the lists needed for fast multipole methods. The algorithms are capable of being efficiently implemented on both serial, data parallel GPU and on distributed architectures. With…

Mathematical Software · Computer Science 2013-01-10 Qi Hu , Nail A. Gumerov , Ramani Duraiswami

Let K be an algebraic number field of degree d and discriminant D over Q. Let A be an associative algebra over K given by structure constants such that A is isomorphic to the algebra M_n(K) of n by n matrices over K for some positive…

Rings and Algebras · Mathematics 2011-12-22 Gábor Ivanyos , Lajos Rónyai , Josef Schicho

A unified fast time-stepping method for both fractional integral and derivative operators is proposed. The fractional operator is decomposed into a local part with memory length $\Delta T$ and a history part, where the local part is…

Numerical Analysis · Mathematics 2017-10-26 Fanhai Zeng , Ian Turner , Kevin Burrage

This article describes a geometric partitioning software that can be used for quick computation of data partitions on many-core HPC machines. It is most suited for dynamic applications with load distributions that vary with time.…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-08-19 Aparna Sasidharan

A method is presented that reduces the number of terms of systems of linear equations (algebraic, ordinary and partial differential equations). As a byproduct these systems have a tendency to become partially decoupled and are more likely…

Symbolic Computation · Computer Science 2007-05-23 Thomas Wolf

This paper introduces the theory and hardware implementation of two new algorithms for computing a single component of the discrete Fourier transform. In terms of multiplicative complexity, both algorithms are more efficient, in general,…

Discrete Mathematics · Computer Science 2018-01-24 G. Jerônimo da Silva , R. M. Campello de Souza , H. M. de Oliveira

In this paper we propose two proximal gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, either…

Optimization and Control · Mathematics 2016-02-01 Radu Ioan Bot , Ernö Robert Csetnek

The works presented in this habilitation concern the algorithmics of polynomials. This is a central topic in computer algebra, with numerous applications both within and outside the field - cryptography, error-correcting codes, etc. For…

Symbolic Computation · Computer Science 2026-03-09 Bruno Grenet

Multidimensional Continued Fraction Algorithms are generalizations of the Euclid algorithm and find iteratively the gcd of two or more numbers. They are defined as linear applications on some subcone of $\mathbb{R}^d$. We consider…

Dynamical Systems · Mathematics 2015-11-30 Sébastien Labbé

In this paper, we extend the work of (Abbondati et al., 2024) on decoding simultaneous rational number codes by addressing two important scenarios: multiplicities and the presence of bad primes (divisors of denominators). First, we…

Information Theory · Computer Science 2025-06-06 Matteo Abbondati , Eleonora Guerrini , Romain Lebreton

We give an algorithm to compute $N$ steps of a convolution quadrature approximation to a continuous temporal convolution using only $O(N \log N)$ multiplications and $O(\log N)$ active memory. The method does not require evaluations of the…

Numerical Analysis · Mathematics 2011-11-10 Achim Schädle , María López-Fernández , Christian Lubich

A fast algorithm for the approximation of a low rank LU decomposition is presented. In order to achieve a low complexity, the algorithm uses sparse random projections combined with FFT-based random projections. The asymptotic approximation…

Numerical Analysis · Mathematics 2016-01-19 Yariv Aizenbud , Gil Shabat , Amir Averbuch

We present in this paper two different classes of general $K$-splitting algorithms for solving finite-dimensional convex optimization problems. Under the assumption that the function being minimized has a Lipschitz continuous gradient, we…

Optimization and Control · Mathematics 2015-03-13 Donald Goldfarb , Shiqian Ma