A new approach to detection of changes in multidimensional patterns

• Autorzy: Gałkowski Tomasz , Krzyżak Adam , Filutowicz Zbigniew

Identyfikatory

DOI

10.2478/jaiscr-2020-0009

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

edge detection; regression; nonparametric estimation

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2020
• Tom: Vol. 10, No. 2
• Strony: 125--136
• Opis fizyczny: Bibliogr. 50 poz., rys.

Twórcy

autor

Gałkowski Tomasz

• Institute of Computational Intelligence Czestochowa University of Technology al. Armii Krajowej 36, PL-42-200 Częstochowa, Poland

autor

Krzyżak Adam

• Department of Computer Science and Software Engineering Concordia University, Montreal, Quebec, Canada H3G 1M8 and Department of Electrical Engineering
• Westpomeranian University of Technology, 70-310 Szczecin, Poland

autor

Filutowicz Zbigniew

• Information Technology Institute University of Social Sciences, 90-113 Łódź
• Clark University Worcester, MA 01610, USA

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).