An important problem in nonlinear science is the unknown parameters estimation in Loranz chaotic system. Clearly, the parameter estimation for chaotic systems is a multidimensional continuous optimization problem, where the optimization goal is to minimize mean squared errors (MSEs) between real and estimated responses for a number of given samples. The Bees algorithm (BA) is a new member of me...

The problem of characterizing those linear systems that exhibit a symmetric behavior was completely solved in the 1D case, ten years ago, in a few papers by F. Fagnani and J. C. Willems. Unfortunately, that theory could not be extended in its full generality to multidimensional systems: the techniques used in the proofs limited the results to systems of independent equations and to a restricted...

We review the relative entropy method in the context of hyperbolic and diffusive relaxation limits of entropy solutions for various hyperbolic models. The main example consists of the convergence from multidimensional compressible Euler equations with friction to the porous medium equation [7]. With small modifications, the arguments used in that case can be adapted to the study of the diffusiv...

Abstract. This paper describes a very flexible "general order" multivariate Padd approximation technique for the model reduction of a multidimensional linear shift-invariant recursive system, i.e., a system characterized by a multivariate rational transfer function. The technique presented allows full control of the regions of support in numerator and denominator of the reduced system and also ...

Our approach to model and represent multidimensional data for explorative data analysis [16] is guided by our experience in the context of epidemiological cancer research. The project CARLOS (Cancer Registry Lower-Saxony) developed the Epidemiological and Statistical Data Exploration System (CARESS) to support multidimensional analysis of health data. The system is based on an architecture that...