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The paper discusses the identification of the empirical, partially intelligible white noise processes generated by deterministic numerical algorithms. The introduced fuzzy‐random complementary approach can identify the inner hidden correlational patterns of the empirical white noise process if the process has a real hidden structure of this kind. We have shown how the characteristics of autocorrelated white noise processes change as the order of autocorrelation increases. Based on this approach, the original empirical white noise process transformed by the autocorrelation operator can be considered to be random data series (randomlikeness), and at the same time, it has function‐like characteristics (functionlikeness), as well. We approach the analysis of the mentioned complementarity by modeling the autocorrelation functions of the empirical white noise processes using tensor product (TP) model transformation. [ABSTRACT FROM AUTHOR]

The paper discusses the identification of the empirical white noise processes generated by deterministic numerical algorithms. The introduced fuzzy-random complementary approach can identify the inner hidden correlational patterns of the empirical white noise process if the process has a real hidden structure of this kind. We have shown how the characteristics of auto-correlated white noise processes change as the order of autocorrelation increases. Although in this paper we rely on random number generators to get approximate white noise processes, in our upcoming research we are planning to turn the focus on physical white noise processes in order to validate our hypothesis. [ABSTRACT FROM AUTHOR]

This paper describes the relation of the higher order singular value decomposition (HOSVD) based canonical form to the Hilbert-Schmidt type integral operators. This connection between the canonical form of f( x) and the integral operators determined by function f( x) is important; on the one hand it gives a new aspect for the consideration of LPV models, and on the other hand it allows for the approximation of eigenfunctions and integral operators based on a numerical reconstruction of the canonical form. [ABSTRACT FROM AUTHOR]

High dynamic range (HDR) of illumination may cause serious distortion and information loss in the viewing and further processing of digital images. On the other hand, digital processing can often improve the visual quality of real-world photographs or views. Recently, HDR imaging techniques have be- come the focus of much research because of their high theoretical and practical importance. If the scene to be viewed or processed has HDR (dark and bright) illumination, these methods are able to help to detect details that a bright environment washes out, and they miss fewer details in a dark environment. By applying HDR techniques, the performance of different image processing and computer vision algorithms, information enhancement, and object and pattern recognition can also be improved. In this paper, a new tone reproduction algorithm is introduced, which may help to develop hard-to-view or nonviewable features and content of color images. The method applies a multiple exposure time image synthesization technique, where the red, green, and blue (RGB) color components of the pixels are separately handled. In the output, the corresponding (modified) color components are blended. As a result, a high-quality color HDR image is obtained, which contains the maximum level of details and color information. [ABSTRACT FROM AUTHOR]

The high dynamic range of illumination may cause serious distortions and problems in the viewing and further processing of digital images. Important information can be hidden in the highly or extremely lowly illuminated parts. This paper deals with the reproduction of such images and introduces two new tone reproduction preprocessing algorithms which may help in developing the hardly viewable or nonviewable features and content of the images. [ABSTRACT FROM AUTHOR]

Car body deformation modeling plays a very important role in crash accident analyses, as well as in safe car body design. The determination of the energy absorbed by the deformation and the corresponding energy equivalent speed can be of key importance; however, their precise determination is a very difficult task. Starting from the results of crash tests, intelligent and soft methods offer a way to model the crash process itself, as well as to determine the absorbed energy, the before-crash speed of the car, etc. In this paper, a modeling technique and an intelligent expert system are introduced, which, together, are able to follow the deformation process of car bodies in car crashes and analyze the strength of the different parts, which can significantly contribute to the improvement of the safety of car bodies. [ABSTRACT FROM AUTHOR]