{"title":"Markovian random fields","authors":"E. Wong","doi":"10.1109/CDC.1984.272296","DOIUrl":null,"url":null,"abstract":"In this paper we examine the Markovian properties of three important random fields: Lévy's Brownian motion, free Euclidean field, and Wiener process. In so doing, we advance the proposition that appropriate candidates for Markov fields are stochastic differential forms and their Markovian property is characterized by being \"one derivative\" removed from white noise.","PeriodicalId":269680,"journal":{"name":"The 23rd IEEE Conference on Decision and Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1984-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 23rd IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1984.272296","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper we examine the Markovian properties of three important random fields: Lévy's Brownian motion, free Euclidean field, and Wiener process. In so doing, we advance the proposition that appropriate candidates for Markov fields are stochastic differential forms and their Markovian property is characterized by being "one derivative" removed from white noise.
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