Convex Combination of Two Diffusion LMS for Distributed Estimation

被引：0
|
作者：
Abadi, Mohammad Shams Esfand [1 ]
Adabi, Ahmad Pour [1 ]
机构：
[1] Shahid Rajaee Teacher Training Univ, Fac Elect Engn, Tehran, Iran
来源：
2019 27TH IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE 2019) | 2019年
关键词：
diffusion LMS; convex combination; diffusion network; tracking performance; ADAPTIVE FILTERING ALGORITHM; LEAST-MEAN SQUARES; PERFORMANCE;
D O I：
10.1109/iraniancee.2019.8786765
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper presents the convex combination of two DLMS (CC-DLMS) algorithms for the distributed estimation problem over diffusion networks. The proposed algorithm has better performance than conventional DLMS algorithm. Also, the tracking capability is improved. In CC-DLMS algorithm, two DLMS algorithms with different step sizes are combined, which results in faster convergence rate as well as lower final error at the price of an increase in complexity. We demonstrate the good performance of the introduced algorithm thorough several simulation results.
引用
收藏
页码：1715 / 1719
页数：5
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