{"title":"多值随机微分方程不变测度的大偏差","authors":"Hua Zhang","doi":"10.1080/07362994.2021.1960565","DOIUrl":null,"url":null,"abstract":"ABSTRACT In this paper, the problem of the large deviations for the invariant measures of the multivalued stochastic differential equations is considered. Under the assumptions of diffusion coefficient being non-Lipschitz and elliptic, we establish the large deviation principle for the invariant measures of the solutions to the multivalued stochastic differential equations. The proof is based on the work of large deviations and invariant measures for the solutions to the multivalued stochastic differential equations.","PeriodicalId":49474,"journal":{"name":"Stochastic Analysis and Applications","volume":"40 1","pages":"798 - 811"},"PeriodicalIF":0.8000,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Large deviations for invariant measures of multivalued stochastic differential equations\",\"authors\":\"Hua Zhang\",\"doi\":\"10.1080/07362994.2021.1960565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT In this paper, the problem of the large deviations for the invariant measures of the multivalued stochastic differential equations is considered. Under the assumptions of diffusion coefficient being non-Lipschitz and elliptic, we establish the large deviation principle for the invariant measures of the solutions to the multivalued stochastic differential equations. The proof is based on the work of large deviations and invariant measures for the solutions to the multivalued stochastic differential equations.\",\"PeriodicalId\":49474,\"journal\":{\"name\":\"Stochastic Analysis and Applications\",\"volume\":\"40 1\",\"pages\":\"798 - 811\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2021-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Stochastic Analysis and Applications\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/07362994.2021.1960565\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Stochastic Analysis and Applications","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/07362994.2021.1960565","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Large deviations for invariant measures of multivalued stochastic differential equations
ABSTRACT In this paper, the problem of the large deviations for the invariant measures of the multivalued stochastic differential equations is considered. Under the assumptions of diffusion coefficient being non-Lipschitz and elliptic, we establish the large deviation principle for the invariant measures of the solutions to the multivalued stochastic differential equations. The proof is based on the work of large deviations and invariant measures for the solutions to the multivalued stochastic differential equations.
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Stochastic Analysis and Applications presents the latest innovations in the field of stochastic theory and its practical applications, as well as the full range of related approaches to analyzing systems under random excitation. In addition, it is the only publication that offers the broad, detailed coverage necessary for the interfield and intrafield fertilization of new concepts and ideas, providing the scientific community with a unique and highly useful service.
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