Optimal State Estimation for Boolean Dynamical Systems using a Boolean Kalman Smoother

被引：0
|
作者：
Imani, Mahdi [1 ]
Braga-Neto, Ulisses [1 ]
机构：
[1] Texas A&M Univ, Dept Elect & Comp Engn, College Stn, TX 77843 USA
来源：
2015 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP) | 2015年
关键词：
Boolean Dynamical System; Boolean Kalman Smoother; Gene Regulatory Network;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper is concerned with state estimation at a fixed time point in a given time series of observations of a Boolean dynamical system. Towards this end, we introduce the Boolean Kalman Smoother, which provides an efficient algorithm to compute the optimal MMSE state estimator for this problem. Performance is investigated using a Boolean network model of the p53-MDM2 negative feedback loop gene regulatory network observed through time series of Next-Generation Sequencing (NGS) data.
引用
收藏
页码：972 / 976
页数：5
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