Automated synthesis of low-rank stochastic dynamical systems using the tensor-train decomposition

For the linear fractional systems of commensurate order, the state space representation is defined as for regular integer state space representation with the state vector

Abstract—In this paper, we propose an improvement of the attack on the Rank Syndrome Decoding (RSD) problem found in [1], usually the best attack considered for evaluating the

2 shows that SSPR has a faster convergence speed when compared to the other methods (for both real and complex cases), since it requires a smaller number of iterations to solve

Keywords: parallel numerical methods · difference scheme · advection equation · time delay.. 1 Introduction and

The primitive BSP EXCHANGE send each state s for a pair (i, s) in tosend to the processor i and returns the set of states received from the other processors, together with the

One of the first contributions to solve the train scheduling or timetabling problems was made by Szpigel [20], he modelled the single track train scheduling problem as a job

We apply the idea of online optimization of RPCA [6] on tensor and update the indi- vidual basis iteratively followed by the processing of one frame per time instance using

Our main contribution is a multiscale approach for solving the unconstrained convex minimization problem introduced in [AHA98], and thus to solve L 2 optimal transport.. Let us