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Wyświetlanie 1-3 z 3
Tytuł:
A new approach to detection of changes in multidimensional patterns
Autorzy:
Gałkowski, Tomasz
Krzyżak, Adam
Filutowicz, Zbigniew
Powiązania:
https://bibliotekanauki.pl/articles/1837532.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
edge detection
regression
nonparametric estimation
Opis:
Nowadays, unprecedented amounts of heterogeneous data collections are stored, processed and transmitted via the Internet. In data analysis one of the most important problems is to verify whether data observed or/and collected in time are genuine and stationary, i.e. the information sources did not change their characteristics. There is a variety of data types: texts, images, audio or video files or streams, metadata descriptions, thereby ordinary numbers. All of them changes in many ways. If the change happens the next question is what is the essence of this change and when and where the change has occurred. The main focus of this paper is detection of change and classification of its type. Many algorithms have been proposed to detect abnormalities and deviations in the data. In this paper we propose a new approach for abrupt changes detection based on the Parzen kernel estimation of the partial derivatives of the multivariate regression functions in presence of probabilistic noise. The proposed change detection algorithm is applied to oneand two-dimensional patterns to detect the abrupt changes.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 2; 125-136
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new approach to detection of changes in multidimensional patterns. Part 2
Autorzy:
Gałkowski, Tomasz
Krzyżak, Adam
Patora-Wysocka, Zofia
Filutowicz, Zbigniew
Wang, Lipo
Powiązania:
https://bibliotekanauki.pl/articles/2031116.pdf
Data publikacji:
2021
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
edge curve detection
regression function
nonparametric estimation
Opis:
In the paper we develop an algorithm based on the Parzen kernel estimate for detection of sudden changes in 3-dimensional shapes which happen along the edge curves. Such problems commonly arise in various areas of computer vision, e.g., in edge detection, bioinformatics and processing of satellite imagery. In many engineering problems abrupt change detection may help in fault protection e.g. the jump detection in functions describing the static and dynamic properties of the objects in mechanical systems. We developed an algorithm for detecting abrupt changes which is nonparametric in nature and utilizes Parzen regression estimates of multivariate functions and their derivatives. In tests we apply this method, particularly but not exclusively, to the functions of two variables.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 3; 217-227
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bandwidth selection for kernel generalized regression neural networks in identification of hammerstein systems
Autorzy:
Lv, Jiaqing
Pawlak, Mirosław
Powiązania:
https://bibliotekanauki.pl/articles/2031118.pdf
Data publikacji:
2021
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
generalized regression neural network
nonparametric estimation
bandwidth
data-driven selection
nonlinear system
Hammerstein system
Opis:
This paper addresses the issue of data-driven smoothing parameter (bandwidth) selection in the context of nonparametric system identification of dynamic systems. In particular, we examine the identification problem of the block-oriented Hammerstein cascade system. A class of kernel-type Generalized Regression Neural Networks (GRNN) is employed as the identification algorithm. The statistical accuracy of the kernel GRNN estimate is critically influenced by the choice of the bandwidth. Given the need of data-driven bandwidth specification we propose several automatic selection methods that are compared by means of simulation studies. Our experiments reveal that the method referred to as the partitioned cross-validation algorithm can be recommended as the practical procedure for the bandwidth choice for the kernel GRNN estimate in terms of its statistical accuracy and implementation aspects.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 3; 181-194
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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