Asymptotically Efficient Recursive Identification Method for FIR System with Quantized Observations

摘要：

　　In this paper,a new recursive identification method is proposed for the FIR linear system with quantized measurements,and without full the information of noise.In this problem,we will try to identify the coefficients of FIR system,the variance of output noise and the threshold of quantized sensor.The maximum likelihood estimate approach is used to deduce the efficient way to identify all unknown parameters of the system.The existence and uniqueness of the estimation is proved,and the Cramér-Rao lower bound of the identification problem is calculated.Then based on some general results on stochastic approximation,we proposed a recursive algorithm,and proved the convergency and asymptotic efficiency of this algorithm.

关键词： System Identification Quantized Observation Stochastic Approximation Convergence Cramer-Rao Lower Bound Asymptotic Efficiency

作者: Xiaolong Yang Hai-Tao Fang

作者单位: Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,P.R.China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 6832-6837

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）