- Tytuł:
- An algorithm for arbitrary-order cumulant tensor calculation in a sliding window of data streams
- Autorzy:
-
Domino, Krzysztof
Gawron, Piotr - Powiązania:
- https://bibliotekanauki.pl/articles/330468.pdf
- Data publikacji:
- 2019
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
high order cumulant
time series statistics
nonnormally distributed data
data streaming
kumulant wysokiego rzędu
szereg czasowy
baza danych rozproszona
strumień danych - Opis:
- High-order cumulant tensors carry information about statistics of non-normally distributed multivariate data. In this work we present a new efficient algorithm for calculation of cumulants of arbitrary orders in a sliding window for data streams. We show that this algorithm offers substantial speedups of cumulant updates compared with the current solutions. The proposed algorithm can be used for processing on-line high-frequency multivariate data and can find applications, e.g., in on-line signal filtering and classification of data streams. To present an application of this algorithm, we propose an estimator of non-Gaussianity of a data stream based on the norms of high order cumulant tensors. We show how to detect the transition from Gaussian distributed data to non-Gaussian ones in a data stream. In order to achieve high implementation efficiency of operations on super-symmetric tensors, such as cumulant tensors, we employ a block structure to store and calculate only one hyper-pyramid part of such tensors.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2019, 29, 1; 195-206
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł