Signal Segmentation using Maximum a Posteriori Probability Estimator

被引：0
|
作者：
Popescu, Theodor D. [1 ]
机构：
[1] Natl Inst Res & Dev Informat, 8-10 Averescu Ave, Bucharest 011455, Romania
来源：
2013 7TH INTERNATIONAL CONFERENCE ON APPLICATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES (AICT) | 2013年
关键词：
Change detection; diagnosis; regression models; decision making; Monte-Carlo simulation; MODELS;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The objective of the paper is to present a segmentation method, using maximum a posteriori probability (MAP) estimator, with application in decision making, based on change detection and diagnosis. Some experimental results obtained by Monte-Carlo simulations for signal segmentation using different signal models, including models with changes in the mean, in FIR, AR and ARX model parameters, that make the object of investigation in other papers, are presented to prove the effectiveness of the approach.
引用
收藏
页码：49 / 53
页数：5
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