基于马尔可夫链蒙特卡罗的相关信号分布式检测(海报)

2018 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA) Pub Date : 2018-06-01 DOI:10.1109/COGSIMA.2018.8423984

Xingjian Sun, Lei Cao, R. Viswanathan

{"title":"基于马尔可夫链蒙特卡罗的相关信号分布式检测(海报)","authors":"Xingjian Sun, Lei Cao, R. Viswanathan","doi":"10.1109/COGSIMA.2018.8423984","DOIUrl":null,"url":null,"abstract":"The distributed detection problem with consideration of correlated sensor observations is an NP-hard problem. In this paper, a heuristic Markov Chain Monte Carlo algorithm, which consists of methods of slice sampling and simulated annealing, is investigated to solve this problem. Based on the criterion of minimizing the probability of error, sub-optimal solutions including fusion rules and sensor decisions are acquired. The performance of this algorithm is studied with analysis of experimental results.","PeriodicalId":231353,"journal":{"name":"2018 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Distributed Detection of Correlated Signal Using Markov Chain Monte Carlo (Poster)\",\"authors\":\"Xingjian Sun, Lei Cao, R. Viswanathan\",\"doi\":\"10.1109/COGSIMA.2018.8423984\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The distributed detection problem with consideration of correlated sensor observations is an NP-hard problem. In this paper, a heuristic Markov Chain Monte Carlo algorithm, which consists of methods of slice sampling and simulated annealing, is investigated to solve this problem. Based on the criterion of minimizing the probability of error, sub-optimal solutions including fusion rules and sensor decisions are acquired. The performance of this algorithm is studied with analysis of experimental results.\",\"PeriodicalId\":231353,\"journal\":{\"name\":\"2018 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COGSIMA.2018.8423984\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COGSIMA.2018.8423984","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

考虑相关传感器观测值的分布式检测问题是一个np困难问题。本文研究了一种启发式马尔可夫链蒙特卡罗算法，该算法由切片采样和模拟退火方法组成。以误差概率最小为准则，获得融合规则和传感器决策的次优解。通过对实验结果的分析，研究了该算法的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Distributed Detection of Correlated Signal Using Markov Chain Monte Carlo (Poster)

The distributed detection problem with consideration of correlated sensor observations is an NP-hard problem. In this paper, a heuristic Markov Chain Monte Carlo algorithm, which consists of methods of slice sampling and simulated annealing, is investigated to solve this problem. Based on the criterion of minimizing the probability of error, sub-optimal solutions including fusion rules and sensor decisions are acquired. The performance of this algorithm is studied with analysis of experimental results.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2018 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)

自引率

0.00%

发文量