{"title":"特征函数在多帧累积算法中的应用","authors":"V. Belokurov, V. I. Koshelev, M. Kagalenko","doi":"10.1109/MECO.2019.8760010","DOIUrl":null,"url":null,"abstract":"This work develops an analytical method of computing detection threshold for multi-frame accumulation. We propose to use characteristic functions for estimating the probability density of statistic on the input of threshold device. The proposed approach is evaluated using chi-squared criterion.","PeriodicalId":141324,"journal":{"name":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The use of Characteristic Functions in the Multi-Frame Accumulation Algorithm\",\"authors\":\"V. Belokurov, V. I. Koshelev, M. Kagalenko\",\"doi\":\"10.1109/MECO.2019.8760010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work develops an analytical method of computing detection threshold for multi-frame accumulation. We propose to use characteristic functions for estimating the probability density of statistic on the input of threshold device. The proposed approach is evaluated using chi-squared criterion.\",\"PeriodicalId\":141324,\"journal\":{\"name\":\"2019 8th Mediterranean Conference on Embedded Computing (MECO)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 8th Mediterranean Conference on Embedded Computing (MECO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MECO.2019.8760010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 8th Mediterranean Conference on Embedded Computing (MECO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MECO.2019.8760010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The use of Characteristic Functions in the Multi-Frame Accumulation Algorithm
This work develops an analytical method of computing detection threshold for multi-frame accumulation. We propose to use characteristic functions for estimating the probability density of statistic on the input of threshold device. The proposed approach is evaluated using chi-squared criterion.