The effective algorithm for constant state detection in time series V 2.3.

The article introduces a simple and effective algorithm for constant state detection in the time series. The algorithm, based on the sliding window of variable length, finds all the sections of the time series which have length greater or equal than some given minimal length and have difference between maximal and minimal value in the section less or equal than some given value. It is shown that the computational complexity of the aforementioned algorithm is O(N log N), where N is the length of time series.

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.28375532.v8
Primary Topic
Time Series Analysis and Forecasting
Type
article
Field-Weighted Citation Impact
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article

The effective algorithm for constant state detection in time series V 2.3.

Figshare
Time Series Analysis and Forecasting
article

The effective algorithm for constant state detection in time series V 2.3.

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Abstract

The article introduces a simple and effective algorithm for constant state detection in the time series. The algorithm, based on the sliding window of variable length, finds all the sections of the time series which have length greater or equal than some given minimal length and have difference between maximal and minimal value in the section less or equal than some given value. It is shown that the computational complexity of the aforementioned algorithm is O(N log N), where N is the length of time series.

Figshare
Openalex Percentile: Top 46%
Time Series Analysis and Forecasting
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The effective algorithm for constant state detection in time series V 2.3. · Figshare (2025) | TGRS Research Map | TGRS