Title :
Unknown noise estimation with DPM model and its application
Author :
Shuxia, Guo ; Bo, Yang ; Ning, Liu
Author_Institution :
Northwestern Polytech. Univ., Xi´´an, China
Abstract :
Dirichlet process mixture (DPM) model, which is the state-of-the-art Bayesian nonparametric model in Statistics, was introduced here. We explored its ability to model and estimate nongaussian unknown noise and applied it to dynamic estimation problem. The algorithm was given and a real world example of GPS estimation problem demonstrated the efficiency of our algorithm.
Keywords :
Bayes methods; noise; nonparametric statistics; Bayesian nonparametric model; DPM model; Dirichlet process mixture model; GPS estimation problem; dynamic estimation problem; nongaussian unknown noise; unknown noise estimation; Bayesian methods; Computational modeling; Estimation; Global Positioning System; Mathematical model; Noise; Signal processing algorithms; Dirichlet Process Mixture; dynamic estimation; multipath; noise estimation;
Conference_Titel :
Wireless Communications and Signal Processing (WCSP), 2010 International Conference on
Conference_Location :
Suzhou
Print_ISBN :
978-1-4244-7556-8
Electronic_ISBN :
978-1-4244-7554-4
DOI :
10.1109/WCSP.2010.5633494
