Open Accessʅ1-Norm Constrained Minimum Eror Entropy Algorithm
Author(s) -
Rajni Yadav,
Chandra Shekhar,
Kanika Agarwal
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c5721.029320
Subject(s) - algorithm , mathematics , gaussian , linear system , entropy (arrow of time) , norm (philosophy) , mathematical optimization , computer science , mathematical analysis , physics , quantum mechanics , political science , law
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.