Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms

• المؤلفون الرئيسيون: Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia
• التنسيق: Proceedings
• اللغة: English; English
• منشور في: IEEE Xplore 2022
• الموضوعات: LB2300-2430 Higher education; TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television
• الوصول للمادة أونلاين: https://eprints.ums.edu.my/id/eprint/41739/3/ABSTRACT%20%286%29.pdf; https://eprints.ums.edu.my/id/eprint/41739/2/FULL%20TEXT.pdf; https://eprints.ums.edu.my/id/eprint/41739/; https://ieeexplore.ieee.org/document/9936845

In diffusion estimation of distributed networks two characteristic parameters are crucial, the speed of convergence and steady-state error. Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. On the contrary, the diffusion normalized s...