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Direct serendipity and mixed finite elements on convex polygons

期刊: NUMERICAL ALGORITHMS, 2023; 92 (2)

We construct new families of direct serendipity and direct mixed finite elements on general planar, strictly convex polygons that are H-1 and H(div) c......

Revisiting the (block) Jacobi subspace rotation method for the symmetric eigenvalue problem

期刊: NUMERICAL ALGORITHMS, 2023; 92 (1)

The paper revisits the topic of block-Jacobi algorithms for the symmetric eigenvalue problem by proposing a few alternative versions. The main advanta......

Estimating the trace of matrix functions with application to complex networks

期刊: NUMERICAL ALGORITHMS, 2023; 92 (1)

The approximation of trace(f(Omega)), where f is a function of a symmetric matrix Omega, can be challenging when Omega is exceedingly large. In such a......

Quantifying mixing in arbitrary fluid domains: a Pade approximation approach

期刊: NUMERICAL ALGORITHMS, 2023; 93 (1)

We consider the model problem of mixing of passive tracers by an incompressible viscous fluid. Addressing questions of optimal control in realistic ge......

On the robustness of exponential base terms and the Pade denominator in some least squares sense

期刊: NUMERICAL ALGORITHMS, 2023; 92 (1)

The exponential analysis of 2n uniformly collected samples from an n-term exponential sum is equivalent to the reconstruction of a rational function o......

Structure-preserving BDF2 FE method for the coupled Schrodinger-Boussinesq equations

期刊: NUMERICAL ALGORITHMS, 2023; 93 (3)

In this article, a structure-preserving second-order backward difference formula (BDF2) finite element (FE) method for finding the numerical solution ......

A survey of mean-square destabilization of multidimensional linear stochastic differential systems with non-normal drift

期刊: NUMERICAL ALGORITHMS, 2023; ()

Mean-square stability analysis of linear stochastic differential systems obtained perturbing ordinary systems by linear terms driven by independent Wi......

A fault detection method based on partition of unity and kernel approximation

期刊: NUMERICAL ALGORITHMS, 2023; ()

In this paper, we present a scattered data approximation method for detecting and approximating the discontinuities of a bivariate function and its gr......

Interpretation of parareal as a two-level additive Schwarz in time preconditioner and its acceleration with GMRES

期刊: NUMERICAL ALGORITHMS, 2023; 94 (1)

We describe an interpretation of parareal as a two-level additive Schwarz preconditioner in the time domain. We show that this two-level preconditione......

A fast and simple algorithm for the computation of the Lerch transcendent

期刊: NUMERICAL ALGORITHMS, 2023; ()

This paper deals with the computation of the Lerch transcendent by means of the Gauss-Laguerre formula. An a priori estimate of the quadrature error, ......

A convex splitting method for the time-dependent Ginzburg-Landau equation

期刊: NUMERICAL ALGORITHMS, 2023; ()

In this paper, we develop a convex splitting algorithm for the time-dependent Ginzburg-Landau equation, which can preserve both the energy stability a......

Hybrid iterative refined restarted Lanczos bidiagonalization methods

期刊: NUMERICAL ALGORITHMS, 2023; 92 (2)

Presented are new hybrid restarted Lanczos bidiagonalization methods for the computation of a few of the extreme singular triplets of very large matri......

Mittag-Leffler stability of numerical solutions to time fractional ODEs

期刊: NUMERICAL ALGORITHMS, 2023; 92 (4)

The asymptotic stable region and long-time decay rate of solutions to linear homogeneous Caputo time fractional ordinary differential equations (F-ODE......

Averaged cubature schemes on the real positive semiaxis

期刊: NUMERICAL ALGORITHMS, 2023; 92 (1)

Stratified cubature rules are proposed to approximate double integrals defined on the real positive semiaxis. In particular, anti-Gauss cubature formu......

A class of new three-term descent conjugate gradient algorithms for large-scale unconstrained optimization and applications to image restoration problems

期刊: NUMERICAL ALGORITHMS, 2023; 93 (3)

Conjugate gradient methods are widely used for solving large-scale unconstrained optimization problems since they have attractive practical factors su......

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