| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 394954 | Information Sciences | 2008 | 7 Pages |
Abstract
This paper studies random weighting estimation of shape and scale parameters in generalized Gaussian distribution (GGD). An expression is established to describe the relationship between moments and parameters. The strong convergence for random weighting estimation of GGD parameters is also rigorously proved. Computational simulations and practical experiments are presented to demonstrate the efficacy for random weighting estimation of GGD parameters.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
SheSheng Gao, Zhihua Feng, Yongmin Zhong, Bijan Shirinzadeh,