{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T17:29:35Z","timestamp":1767374975641,"version":"build-2065373602"},"reference-count":67,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,10,18]],"date-time":"2019-10-18T00:00:00Z","timestamp":1571356800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100014440","name":"Ministerio de Ciencia, Innovaci\u00f3n y Universidades","doi-asserted-by":"publisher","award":["PTQ\u201316\u201308538"],"award-info":[{"award-number":["PTQ\u201316\u201308538"]}],"id":[{"id":"10.13039\/100014440","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Many measures to quantify the nonlinear dynamics of a time series are based on estimating the probability of certain features from their relative frequencies. Once a normalised histogram of events is computed, a single result is usually derived. This process can be broadly viewed as a nonlinear      I  R  n     mapping into     I  R    , where n is the number of bins in the histogram. However, this mapping might entail a loss of information that could be critical for time series classification purposes. In this respect, the present study assessed such impact using permutation entropy (PE) and a diverse set of time series. We first devised a method of generating synthetic sequences of ordinal patterns using hidden Markov models. This way, it was possible to control the histogram distribution and quantify its influence on classification results. Next, real body temperature records are also used to illustrate the same phenomenon. The experiments results confirmed the improved classification accuracy achieved using raw histogram data instead of the PE final values. Thus, this study can provide a very valuable guidance for the improvement of the discriminating capability not only of PE, but of many similar histogram-based measures.<\/jats:p>","DOI":"10.3390\/e21101013","type":"journal-article","created":{"date-parts":[[2019,10,18]],"date-time":"2019-10-18T11:24:15Z","timestamp":1571397855000},"page":"1013","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Permutation Entropy: Enhancing Discriminating Power by Using Relative Frequencies Vector of Ordinal Patterns Instead of Their Shannon Entropy"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0076-0515","authenticated-orcid":false,"given":"David","family":"Cuesta-Frau","sequence":"first","affiliation":[{"name":"Technological Institute of Informatics, Universitat Polit\u00e8cnica de Val\u00e8ncia, 03801 Alcoi Campus, Spain"},{"name":"Innovatec Sensorizaci\u00f3n y Comunicaci\u00f3n S.L., Avda. Elx, 3, 03801 Alcoi, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio","family":"Molina-Pic\u00f3","sequence":"additional","affiliation":[{"name":"Technological Institute of Informatics, Universitat Polit\u00e8cnica de Val\u00e8ncia, 03801 Alcoi Campus, Spain"},{"name":"Innovatec Sensorizaci\u00f3n y Comunicaci\u00f3n S.L., Avda. Elx, 3, 03801 Alcoi, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5553-8372","authenticated-orcid":false,"given":"Borja","family":"Vargas","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, M\u00f3stoles Teaching Hospital, M\u00f3stoles, 28935 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6523-8704","authenticated-orcid":false,"given":"Paula","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, M\u00f3stoles Teaching Hospital, M\u00f3stoles, 28935 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,10,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"12:1","DOI":"10.1145\/2379776.2379788","article-title":"Time-series Data Mining","volume":"45","author":"Esling","year":"2012","journal-title":"ACM Comput. 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