File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/ICDSP.2002.1028178
- Scopus: eid_2-s2.0-30344478663
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: Convergence analysis of the recursive least M-estimate adaptive filtering algorithm for impulse noise suppression
| Title | Convergence analysis of the recursive least M-estimate adaptive filtering algorithm for impulse noise suppression |
|---|---|
| Authors | |
| Issue Date | 2002 |
| Publisher | IEEE. |
| Citation | The 14th International Conference on Digital Signal Processing, Santorini, Greece, 1-3 July 2002, v. 2, p. 663-666 How to Cite? |
| Abstract | We present the convergence analysis of the recursive least M-estimate (RLM) adaptive filter algorithm, which was recently proposed for robust adaptive filtering in the impulse noise environment. The mean and mean squares behaviors of the RLM algorithm, based on the modified Huber M-estimate function (MHF), in the contaminated Gaussian (CG) noise model are analyzed. Close-form expressions are derived. The simulation and theoretical results agree very well with each other and suggest that the RLM algorithm is more robust than the RLS algorithm under the CG noise model. |
| Persistent Identifier | http://hdl.handle.net/10722/46392 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Chan, SC | en_HK |
| dc.contributor.author | Zou, YX | en_HK |
| dc.date.accessioned | 2007-10-30T06:48:53Z | - |
| dc.date.available | 2007-10-30T06:48:53Z | - |
| dc.date.issued | 2002 | en_HK |
| dc.identifier.citation | The 14th International Conference on Digital Signal Processing, Santorini, Greece, 1-3 July 2002, v. 2, p. 663-666 | en_HK |
| dc.identifier.uri | http://hdl.handle.net/10722/46392 | - |
| dc.description.abstract | We present the convergence analysis of the recursive least M-estimate (RLM) adaptive filter algorithm, which was recently proposed for robust adaptive filtering in the impulse noise environment. The mean and mean squares behaviors of the RLM algorithm, based on the modified Huber M-estimate function (MHF), in the contaminated Gaussian (CG) noise model are analyzed. Close-form expressions are derived. The simulation and theoretical results agree very well with each other and suggest that the RLM algorithm is more robust than the RLS algorithm under the CG noise model. | en_HK |
| dc.format.extent | 350921 bytes | - |
| dc.format.extent | 27162 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.format.mimetype | text/plain | - |
| dc.language | eng | en_HK |
| dc.publisher | IEEE. | en_HK |
| dc.relation.ispartof | International Conference on Digital Signal Processing | - |
| dc.rights | ©2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
| dc.title | Convergence analysis of the recursive least M-estimate adaptive filtering algorithm for impulse noise suppression | en_HK |
| dc.type | Conference_Paper | en_HK |
| dc.description.nature | published_or_final_version | en_HK |
| dc.identifier.doi | 10.1109/ICDSP.2002.1028178 | en_HK |
| dc.identifier.scopus | eid_2-s2.0-30344478663 | - |
| dc.identifier.hkuros | 82533 | - |