ML-DC ALGORITHM OF PARAMETER ESTIMATION FOR GAUSSIAN MIXTURE AUTOREGRESSIVE MODEL

摘要：

With Gaussian mixture autoregressive model, the probability density and power spectrum density of non- Gaussian colored processes can be fit.Its parameters can be estimated through the ML-DC algorithm.After descriptions of the model and the estimation problem, maximum likelihood estimation of autoregressive parameters and the dynamic clutter algorithm for Gaussian mixture parameters are deduced, respectively.Based on them, ML-DC algorithm for coupling estimation between power spectrum density parameters and probability density parameters is built up.Finally, a numerical instance in simulation is illustrated where performance of estimation is discussed in detail.

关键词： Gaussian mixture autoregressive model Maximum likelihood estimation Dynamic clutter algorithm

作者: LIU FENG MA CHAOYANG WANG PINGBO HONG LIXUE

作者单位: Naval University of Engineering,Wuhan,China Navy Force No.92910,Zhoushan,China Navy Force No.91267,Fuzhou,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Technology and Development(2011第三届计算机技术与发展国际会议 ICCTD2011)

会议地点: 成都

会议语种:英文

页码: 1030-1036

在线出版日期: 2011-11-25（万方平台首次上网日期，不代表论文的发表时间）