Name
Abstract | ||
|---|---|---|
A novel adaptive filtering (AF) algorithm is proposed for group-sparse system identifications. In the devised algorithm, a novel mixed error criterion (MEC) with two-order logarithm error, p-order errors and group sparse constraint method is devised to give a resistant to the impulsive noise. The proposed group-sparse MEC can fully use the known group-sparse characteristics in the cluster sparse systems, and it is derived and analyzed in detail. Various simulations are presented and analyzed to give a verification on the effectiveness of the developed group-sparse MEC algorithms, and the simulated results shown that the developed algorithm outperforms the previously developed sparse AF algorithms for identifying the systems. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/sym11050697 | SYMMETRY-BASEL |
Keywords | Field | DocType |
system identification,group sparse constraint,mixed error criterion,impulsive noise environments | Combinatorics,Adaptive filtering algorithm,Algorithm,Adaptive filter,Logarithm,System identification,Mathematics | Journal |
Volume | Issue | Citations |
11 | 5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yingsong Li | 1 | 120 | 34.72 |
| Aleksey Cherednichenko | 2 | 0 | 0.68 |
| Zhengxiong Jiang | 3 | 1 | 2.46 |
| Wanlu Shi | 4 | 1 | 3.73 |
| Jinqiu Wu | 5 | 1 | 1.72 |