File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/APCCAS.2008.4745994
- Scopus: eid_2-s2.0-62949112559
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: A new noise-constrained normalized least mean squares adaptive filtering algorithm
Title | A new noise-constrained normalized least mean squares adaptive filtering algorithm |
---|---|
Authors | |
Keywords | Adaptive Filtering Adaptive Filters Convergence Of Numerical Methods Impulse Noise Impulse Response |
Issue Date | 2008 |
Citation | The 2008 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS 2008 ), Macao, China, 30 November-3 December 2008. In Conference Proceedings, 2008, p. 197-200 How to Cite? |
Abstract | This paper proposes a new noise-constrained normalized least mean squares (NC-NLMS) adaptive filtering algorithm and studies its mean and mean square convergence behaviors. The new NC-NLMS algorithm is obtained by extending the noise-constrained LMS (NC-LMS) algorithm of Wei [1], which was proposed to explore the prior information on the noise variance in identifying unknown finite impulse response channels. It gives rise to a variable step-size LMS algorithm that is capable of achieving better tradeoff between the requirements to maximize convergence rate and to minimize misadjustment. Using a novel transformation approach, a new NC-NLMS algorithm is derived based on the NC-LMS framework. Additionally, robust statistics technique is employed to improve the robustness of the NC-NLMS algorithm in impulsive noise environment. Simulation shows that the proposed NC-NLMS offers improved performance than the NC-LMS algorithm due to the data normalization and its robust version can achieve satisfactory performance against impulse noise. Extension to the least M-estimate (LMM) and normalized least M-estimate (NLMM) algorithms were also proposed. © 2008 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/143330 |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chan, SC | en_HK |
dc.contributor.author | Zhang, ZG | en_HK |
dc.contributor.author | Zhou, Y | en_HK |
dc.contributor.author | Hu, Y | en_HK |
dc.date.accessioned | 2011-11-22T08:30:36Z | - |
dc.date.available | 2011-11-22T08:30:36Z | - |
dc.date.issued | 2008 | en_HK |
dc.identifier.citation | The 2008 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS 2008 ), Macao, China, 30 November-3 December 2008. In Conference Proceedings, 2008, p. 197-200 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/143330 | - |
dc.description.abstract | This paper proposes a new noise-constrained normalized least mean squares (NC-NLMS) adaptive filtering algorithm and studies its mean and mean square convergence behaviors. The new NC-NLMS algorithm is obtained by extending the noise-constrained LMS (NC-LMS) algorithm of Wei [1], which was proposed to explore the prior information on the noise variance in identifying unknown finite impulse response channels. It gives rise to a variable step-size LMS algorithm that is capable of achieving better tradeoff between the requirements to maximize convergence rate and to minimize misadjustment. Using a novel transformation approach, a new NC-NLMS algorithm is derived based on the NC-LMS framework. Additionally, robust statistics technique is employed to improve the robustness of the NC-NLMS algorithm in impulsive noise environment. Simulation shows that the proposed NC-NLMS offers improved performance than the NC-LMS algorithm due to the data normalization and its robust version can achieve satisfactory performance against impulse noise. Extension to the least M-estimate (LMM) and normalized least M-estimate (NLMM) algorithms were also proposed. © 2008 IEEE. | en_HK |
dc.language | eng | en_US |
dc.relation.ispartof | Proceedings of IEEE Asia-Pacific Conference on Circuits & Systems, APCCAS 2008 | en_HK |
dc.subject | Adaptive Filtering | en_US |
dc.subject | Adaptive Filters | en_US |
dc.subject | Convergence Of Numerical Methods | en_US |
dc.subject | Impulse Noise | en_US |
dc.subject | Impulse Response | en_US |
dc.title | A new noise-constrained normalized least mean squares adaptive filtering algorithm | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Chan, SC: ascchan@hkucc.hku.hk | en_HK |
dc.identifier.email | Zhang, ZG: zhangzg@hku.hk | en_HK |
dc.identifier.email | Zhou, Y: yizhou@eee.hku.hk | en_HK |
dc.identifier.email | Hu, Y: yhud@hku.hk | en_HK |
dc.identifier.authority | Chan, SC=rp00094 | en_HK |
dc.identifier.authority | Zhang, ZG=rp01565 | en_HK |
dc.identifier.authority | Zhou, Y=rp00213 | en_HK |
dc.identifier.authority | Hu, Y=rp00432 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1109/APCCAS.2008.4745994 | en_HK |
dc.identifier.scopus | eid_2-s2.0-62949112559 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-62949112559&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.spage | 197 | en_HK |
dc.identifier.epage | 200 | en_HK |
dc.identifier.scopusauthorid | Chan, SC=13310287100 | en_HK |
dc.identifier.scopusauthorid | Zhang, ZG=8597618700 | en_HK |
dc.identifier.scopusauthorid | Zhou, Y=55209555200 | en_HK |
dc.identifier.scopusauthorid | Hu, Y=7407116091 | en_HK |
dc.customcontrol.immutable | sml 170512 amended | - |