Szczegóły publikacji
Opis bibliograficzny
A two-level detector of short-term unique changes in time series based on a similarity method / Tomasz PEŁECH-PILICHOWSKI, Jan T. DUDA // Expert Systems ; ISSN 0266-4720. — 2015 — vol. 32 no. 4, s. 555–561. — Bibliogr. s. 561, Abstr.
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 91285 |
|---|---|
| Data dodania do BaDAP | 2015-08-25 |
| Tekst źródłowy | URL |
| DOI | 10.1111/j.1468-0394.2012.00629.x |
| Rok publikacji | 2015 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Expert Systems |
Abstract
In the paper, a novel two-level algorithm of time-series change detection is presented. In the first level, to identify non-stationary sequences in a processed signal, preliminary detection of events is performed with a short-term prediction comparison. In the second stage, to confirm the changes detected in the first level, a similarity method aimed at identification of unique changes is employed. The detection of changes in a non-stationary time series is discussed, implemented algorithms are described and the results produced on a sample four financial time series are shown. General conditions for implementing the proposed algorithm as an immune-like event detector are discussed.