Name
Title | ||
|---|---|---|
Low-complexity correlated time-averaged variable forgetting factor mechanism for diffusion RLS algorithm in sensor networks |
Abstract | ||
|---|---|---|
In this work, we present the low-complexity variable forgetting factor (VFF) technique for the diffusion recursive least squares (RLS) algorithm. In particular, we adopt the VFF mechanism that rely on time-averages of the posteriori error signal and incorporate it into the diffusion RLS (DRLS) algorithm to yield the low-complexity correlated time-averaged VFF diffusion RLS (LCTVFF-DRLS) algorithm. We develop detailed analyses in terms of mean and mean square performance for the proposed algorithm, and derive mathematical expressions to compute the mean square deviation (MSD) and the excess mean square error (EMSE). The simulation results show that the proposed LCTVFF-DRLS algorithm outperforms the existing DRLS algorithm with the fixed forgetting factor, and demonstrate a good match between our proposed analytical expressions and simulated results. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/SAM.2016.7569612 | 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) |
Keywords | Field | DocType |
Sensor networks,distributed estimation,diffusion recursive least-squares,variable forgetting factor | Mean square,Excess mean square error,Forgetting factor,Mathematical optimization,Expression (mathematics),Error signal,Root-mean-square deviation,Statistics,Wireless sensor network,Mathematics,Recursive least squares filter | Conference |
ISBN | Citations | PageRank |
978-1-5090-2104-8 | 1 | 0.36 |
References | Authors | |
12 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ling Zhang | 1 | 7 | 1.41 |
| Yunlong Cai | 2 | 86 | 11.26 |
| Chunguang Li | 3 | 748 | 63.37 |
| Rodrigo C. de Lamare | 4 | 1461 | 179.59 |
| Minjian Zhao | 5 | 224 | 34.77 |