{"title":"Convergence characteristics at stochastic estimation of image inter-frame deformations","authors":"A. Tashlinskii, A. Zhukova, D. Kraus","doi":"10.18287/1613-0073-2019-2391-114-120","DOIUrl":null,"url":null,"abstract":"Several approaches to the numerical description of image inter-frame geometric deformations parameters estimates behavior at iterations of non-identification relay stochastic gradient estimation are considered. The probability density of the Euclidean mismatch distance of estimates vector is chosen as an argument of the characteristics forming the numerical values. It made it possible to ensure invariance of research to the set of parameters of the used inter-frame geometric deformations model. The mathematical expectation, the probability of exceeding a given threshold value of the convergence rate and the confidence interval of the Euclidean mismatch distance were investigated as characteristics. Probabilistic mathematical modeling is applied to calculate the probability density of the Euclidean mismatch distance.","PeriodicalId":10486,"journal":{"name":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Collection of selected papers of the III International Conference on Information Technology and Nanotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18287/1613-0073-2019-2391-114-120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Several approaches to the numerical description of image inter-frame geometric deformations parameters estimates behavior at iterations of non-identification relay stochastic gradient estimation are considered. The probability density of the Euclidean mismatch distance of estimates vector is chosen as an argument of the characteristics forming the numerical values. It made it possible to ensure invariance of research to the set of parameters of the used inter-frame geometric deformations model. The mathematical expectation, the probability of exceeding a given threshold value of the convergence rate and the confidence interval of the Euclidean mismatch distance were investigated as characteristics. Probabilistic mathematical modeling is applied to calculate the probability density of the Euclidean mismatch distance.