scholarly journals Minimum error entropy criterion‐based randomised autoencoder

Author(s):  
Rongzhi Ma ◽  
Tianlei Wang ◽  
Jiuwen Cao ◽  
Fang Dong
2019 ◽  
Vol 26 (2) ◽  
pp. 347-351 ◽  
Author(s):  
Badong Chen ◽  
Rongjin Ma ◽  
Siyu Yu ◽  
Shaoyi Du ◽  
Jing Qin

Entropy ◽  
2012 ◽  
Vol 14 (11) ◽  
pp. 2311-2323 ◽  
Author(s):  
Badong Chen ◽  
Jose Principe

This work proposes a linear phase sparse minimum error entropy adaptive filtering algorithm. The linear phase condition is obtained by considering symmetry or anti symmetry condition onto the system coefficients. The proposed work integrates linear constraint based on linear phase of the system and -norm for sparseness into minimum error entropy adaptive algorithm. The proposed -norm linear constrained minimum error entropy criterion ( -CMEE) algorithm makes use of high-order statistics, hence worthy for non-Gaussian channel noise. The experimental results obtained for linear phase sparse system identification in the presence of non-Gaussian channel noise reveal that the proposed algorithm has lower steady state error and higher convergence rate than other existing MEE variants.


2007 ◽  
Vol 87 (11) ◽  
pp. 2733-2745 ◽  
Author(s):  
Seungju Han ◽  
Sudhir Rao ◽  
Deniz Erdogmus ◽  
Kyu-Hwa Jeong ◽  
Jose Principe

2020 ◽  
Vol 172 ◽  
pp. 107534
Author(s):  
Zhuang Li ◽  
Lei Xing ◽  
Badong Chen

2019 ◽  
Vol 52 (24) ◽  
pp. 93-97
Author(s):  
Zejun Chen ◽  
Haiquan Zhao

Sign in / Sign up

Export Citation Format

Share Document