Abstract. This paper contributes to the study of Freely Rewriting Restarting Automata (FRR-automata) and Parallel Communicating Grammar Systems (PCGS), which both are useful models in computational linguistics. For PCGS we study two complexity measures called generation complexity and distribution complexity, and we prove that a PCGS Π , for which the generation complexity and the distribution ...

In this contribution, a way to enhance the performance of the classic Genetic Algorithm is proposed. The idea of restarting a Genetic Algorithm is applied in order to obtain better knowledge of the solution space of the problem. A new operator of “insertion” is introduced so as to exploit (utilize) the information that has already been collected before the restarting procedure. Finally, numeric...

Modelica’s language support includes so-called events for describing discontinuities. Modern integrating environments, like Assimulo, provide elaborate event detection and event handling methods. In addition, the overall performance of a simulation of models with discontinuities (hybrid models) depends strongly on the methods for restarting the integration after an event detection. The present ...

We consider the class of the Orthogonal Projection Methods (OPM) to solve iteratively large and generalised eigenvalue problems. An OPM is a method that projects a large eigenvalue problem on a smaller subspace. In this subspace, an approximation of the eigenvalue spectrum can be computed from a small eigenvalue problem using a direct method. We show that many iterative eigenvalue solvers, such...

In this text, we present a generalisation of the idea of the Implicitly Restarted Arnoldi method to the nonsymmetric Lanczos algorithm, using the two-sided Gram-Schmidt process or using a full Lanczos tridi-agonalisation. The Implicitly Restarted Lanczos method can be combined with an implicit lter. It can also be used in case of breakdown and ooers an alternative for look-ahead.

Exponential integrator (EI) method based on Krylov subspace approximation is a promising for large-scale transient circuit simulation. However, it suffers from the singularity problem and consumes large dimensions stiff circuits when using ordinary subspace. Restarting schemes are commonly applied to reduce dimension, but they also slow down convergence degrade overall computational efficiency....