Waveform relaxation techniques have become increasingly important with the wide
availability of parallel computers with a large number of processors. A limiting factor for …

Waveform relaxation (WR) is a technique that can be used to solve large systems of ordinary
differential equations (ODEs). It is particularly suitable for the parallel solution of ODEs with …

The longitudinal waveform relaxation (WR) proposed by Gander and Ruehli converges
faster than the classical WR method. For the former, a free parameter α is contained, which …

The optimized waveform relaxation (OWR) methods, benefiting from intelligent information
exchange between subsystems–the so-called transmission conditions (TCs), are recognized …

For time dependent problems, the Schwarz waveform relaxation (SWR) algorithm can be
analyzed both at the continuous and semi-discrete level. For consistent space …

Waveform relaxation techniques are an important tool for the simulation of very large scale
circuits. They are based on a partition of the circuit into sub-circuits, and then use an iteration …

Convergence rate is greatly improved by using the new waveform relaxation (WR) methods,
known as optimized waveform relaxation (OWR) algorithms, over the classical ones due to …

A parallel waveform relaxation (WR) algorithm is presented for transient analysis of large
distributed interconnect networks. The proposed algorithm partitions interconnect circuits …

The Schwarz waveform relaxation (SWR) algorithms have many favorable properties and
are extensively studied and investigated for solving time dependent problems mainly at a …

In this paper, we investigate the convergence behavior of the Schwarz waveform relaxation
(SWR) algorithm for partial neutral functional differential equations which arise from lossless …