Title
Expectation maximization estimation algorithm for Hammerstein models with non-Gaussian noise and random time delay from dual-rate sampled-data.
Abstract
This paper considers the robust identification for dual-rate input nonlinear equation-error systems with outliers and random time delay. To suppress the negative influence caused by the outliers to the accuracy of identification, the distribution of the noise is represented by a t-distribution rather than a Gaussian distribution. A random time delay is considered in the dual-rate input nonlinear systems. By treating the unknown time delay as the latent variable, the expectation maximization algorithm is derived for identifying the systems. Two numerical simulation examples demonstrate that the proposed algorithm can generate accurate identification results when the measurements are contaminated by the outliers.
Year
DOI
Venue
2018
10.1016/j.dsp.2017.11.009
Digital Signal Processing
Keywords
Field
DocType
Non-Gaussian noise,Time delay,Expectation maximization,Parameter estimation,Input nonlinear system
Mathematical optimization,Nonlinear system,Computer simulation,Expectation–maximization algorithm,Outlier,Algorithm,Latent variable,Gaussian,Estimation theory,Gaussian noise,Mathematics
Journal
Volume
ISSN
Citations 
73
1051-2004
1
PageRank 
References 
Authors
0.35
22
4
Name
Order
Citations
PageRank
Junxia Ma1839.39
Jing Chen2269.68
Weili Xiong3285.92
Feng Ding44973231.42