Acceleration of time series entropy algorithms
| Autor: | Jiří Tomčala |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
020203 distributed computing
Computer science Entropy (statistical thermodynamics) 02 engineering and technology Approximate entropy Theoretical Computer Science Sample entropy Entropy estimation Entropy (classical thermodynamics) Hardware and Architecture 0202 electrical engineering electronic engineering information engineering Entropy (information theory) Entropy (energy dispersal) Entropy (arrow of time) Time complexity Algorithm Software Information Systems Entropy (order and disorder) |
| Zdroj: | The Journal of Supercomputing. 75:1443-1454 |
| ISSN: | 1573-0484 0920-8542 |
| DOI: | 10.1007/s11227-018-2657-2 |
| Popis: | This paper concentrates on the entropy estimation of time series. Two new algorithms are introduced: Fast Approximate Entropy and Fast Sample Entropy. Their main advantage is their lower time complexity. Examples considered in the paper include interesting experiments with real-world data obtained from IT4Innovations’ supercomputers Salomon and Anselm, as well as with data artificially created specifically to test the credibility of these new entropy analyzers. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|