This paper develops a predictive modeling algorithm, denoted as Real-Time Vector Fitting (RTVF), which is capable of approximating the real-time linearized dynamics multi-input multi-output (MIMO) dynamical systems via rational transfer function matrices. Based on generalization well-known Time-Domain (TDVF) RTVF suitable for online experience both initial-state decay contributions in measured ...

System identification (SI) techniques can be used to identify the dynamic parameters of mechanical systems and civil infrastructures. The aim is rapidly consistently model object interest, in a quantitative principled manner. This also useful establishing capacity structure serve its purpose, thus as tool for structural health monitoring (SHM). In this context, input–output SI allow precise rob...

In Functional Data Analysis (FDA) multivariate data are considered as sampled functions. We propose a non-supervised method for finding a good function basis that is built on the data set. The basis consists of a set of Gaussian kernels that are optimized for an accurate fitting. The proposed methodology is experimented with two spectrometric data sets. The obtained weights are further scaled u...

The present work introduces a modified scheme for the solution of compressible 2-D full Navier-Stokes equations, using Flux Vector Splitting method. As a result of this modification, numerical diffusion is reduced. The computer code which is developed based on this algorithm can be used easily and accurately to analyze complex flow fields with discontinuity in properties, in cases such as shock...

I show an example of how the principal component analysis method can be used for solving a specific computer vision problem—the one of fitting an ellipse to a set of points. In the example, the feature map is given (postulated) as part of the problem specification. More generally, the feature map in the kernel principal component analysis has the interpretation of the model class in data modell...