Nested Pattern Detection and Unidimensional Process Characterization

Autor: Gerardo L. Febres
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Entropy, Vol 26, Iss 9, p 754 (2024)
Druh dokumentu: article
ISSN: 1099-4300
DOI: 10.3390/e26090754
Popis: This document introduces methods for describing long texts as groups of repeating symbols or patterns. The process converts a series of real-number values into texts. Developed tailored algorithms for identifying repeated sequences in the text are applied to decompose the text into nested tree-like structures of repeating symbols and is called the Nested Repeated Sequence Decomposition Model (NRSDM). The NRSDM is especially valuable for extracting repetitive behaviors in oscillatory but non-periodic and chaotic processes where the classical Fourier transform has limited application. The NRSDM along with the two graphical representations proposed here form a promising tool for characterizing long texts configured to represent the behavior of unidimensional processes.
Databáze: Directory of Open Access Journals
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