Name
Abstract | ||
|---|---|---|
The design of variable span linear filters for noise reduction involves a generalized eigenvalue decomposition problem that is of high computational complexity. In order to address this issue, this work proposes a recursive algorithm that computes the filter weights with streaming signal data. Specifically, the inverse square root of the noise covariance matrix is recursively computed with a rank-... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LSP.2019.2953817 | IEEE Signal Processing Letters |
Keywords | Field | DocType |
Covariance matrices,Eigenvalues and eigenfunctions,Noise reduction,Noise measurement,Acoustic distortion,Computational complexity | Noise reduction,Linear filter,Pattern recognition,Algorithm,Artificial intelligence,Mathematics,Recursion | Journal |
Volume | Issue | ISSN |
26 | 12 | 1070-9908 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yingke Zhao | 1 | 0 | 1.01 |
| Jie Chen | 2 | 34 | 11.39 |
| Jingdong Chen | 3 | 11 | 3.29 |