{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:17:46Z","timestamp":1760242666387,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2016,1,20]],"date-time":"2016-01-20T00:00:00Z","timestamp":1453248000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science and Technology Program","award":["2013GS500303"],"award-info":[{"award-number":["2013GS500303"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61105093"],"award-info":[{"award-number":["61105093"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Science and Technology Projects of CSTC","award":["CSTC2012GG-YYJSB40001, CSTC2013-JCS F40009"],"award-info":[{"award-number":["CSTC2012GG-YYJSB40001, CSTC2013-JCS F40009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector\u2019s false alarms.<\/jats:p>","DOI":"10.3390\/s16010126","type":"journal-article","created":{"date-parts":[[2016,1,20]],"date-time":"2016-01-20T11:19:41Z","timestamp":1453288781000},"page":"126","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals"],"prefix":"10.3390","volume":"16","author":[{"given":"Jiaduo","family":"Zhao","sequence":"first","affiliation":[{"name":"Key Lab of Optoelectronic Technology and Systems, Chongqing University, 174 Shazheng Street, Chongqing 400044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiguo","family":"Gong","sequence":"additional","affiliation":[{"name":"Key Lab of Optoelectronic Technology and Systems, Chongqing University, 174 Shazheng Street, Chongqing 400044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuzhen","family":"Tang","sequence":"additional","affiliation":[{"name":"Technology Center of Sichuan Changhong Electric Co. 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