Proposed hybrid sparse adaptive algorithms for system identification
Other Title(s)
الخوارزميات التكيفية الهجينة المقترحة لتحديد هوية الأنظمة التكيفية المتناثرة
Joint Authors
Abd al-Sattar, Mahmud Abd al-Qadir
Ali, Samir Husayn
Source
al-Khwarizmi Engineering Journal
Issue
Vol. 13, Issue 2 (30 Jun. 2017), pp.62-69, 8 p.
Publisher
University of Baghdad al-Khwarizmi College of Engineering
Publication Date
2017-06-30
Country of Publication
Iraq
No. of Pages
8
Main Subjects
Abstract EN
For sparse system identification, recent suggested algorithms are ^0-nonn Least Mean Square (f0-LMS), Zero- Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity.
And so, the proposed algorithms are named ?0‘ZA-LMS.
/VRZA-LMS.
p-ZA-LMS and p-RZA-LMS that are designed by merging twoconstraints from previous algorithms to improve theconvergence rate and steady state of MSD for sparse system In this paper, a complete analysis was done for the theoretical operation of proposed algorithms by exited white Gaussian sequence for input signal.
The discussion of mean square deviation (MSD) with regard to parameters of algorithms and system sparsity was observed.
In addition, in this paper, the correlation between proposed algorithms and the last recent algorithms were presented and th|e necessary conditions of these proposed algorithms were planned to improve convergence rate.
Finally, the results of simulations are compared with theoretical study (?), which is presented to match closely by a wide-range of parameters..
American Psychological Association (APA)
Abd al-Sattar, Mahmud Abd al-Qadir& Ali, Samir Husayn. 2017. Proposed hybrid sparse adaptive algorithms for system identification. al-Khwarizmi Engineering Journal،Vol. 13, no. 2, pp.62-69.
https://search.emarefa.net/detail/BIM-838183
Modern Language Association (MLA)
Abd al-Sattar, Mahmud Abd al-Qadir& Ali, Samir Husayn. Proposed hybrid sparse adaptive algorithms for system identification. al-Khwarizmi Engineering Journal Vol. 13, no. 2 (2017), pp.62-69.
https://search.emarefa.net/detail/BIM-838183
American Medical Association (AMA)
Abd al-Sattar, Mahmud Abd al-Qadir& Ali, Samir Husayn. Proposed hybrid sparse adaptive algorithms for system identification. al-Khwarizmi Engineering Journal. 2017. Vol. 13, no. 2, pp.62-69.
https://search.emarefa.net/detail/BIM-838183
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 67-68
Record ID
BIM-838183