Generalized Robust Multichannel Frequency‐Domain LMS Algorithms for Blind Channel Identification
Recently, several noise‐robust adaptive multichannel LMS algorithms have been proposed based on the spectral flatness of the estimated channel coefficients in the presence of additive noise. In this work, we propose a general form for the algorithms that integrates the existing algorithms into a com...
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| Published in | ETRI journal Vol. 34; no. 1; pp. 130 - 133 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
한국전자통신연구원
01.02.2012
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1225-6463 2233-7326 |
| DOI | 10.4218/etrij.12.0211.0118 |
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| Abstract | Recently, several noise‐robust adaptive multichannel LMS algorithms have been proposed based on the spectral flatness of the estimated channel coefficients in the presence of additive noise. In this work, we propose a general form for the algorithms that integrates the existing algorithms into a common framework. Computer simulation results are presented and demonstrate that a new proposed algorithm gives better performance compared to existing algorithms in noisy environments. |
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| AbstractList | Recently, several noise‐robust adaptive multichannel LMS algorithms have been proposed based on the spectral flatness of the estimated channel coefficients in the presence of additive noise. In this work, we propose a general form for the algorithms that integrates the existing algorithms into a common framework. Computer simulation results are presented and demonstrate that a new proposed algorithm gives better performance compared to existing algorithms in noisy environments. Power metal-oxide semiconductor field-effect transistor (MOSFET) devices are widely used in power electronics applications, such as brushless direct current motors and power modules. For a conventional power MOSFET device such as trench double-diffused MOSFET (TDMOS), there is a tradeoff relationship between specific on-state resistance and breakdown voltage. To overcome the tradeoff relationship, a super-junction (SJ) trench MOSFET (TMOSFET) structure is studied and designed in this letter. The processing conditions are proposed, and studies on the unit cell are performed for optimal design. The structure modeling and the characteristic analyses for doping density, potential distribution, electric field, width, and depth of trench in an SJ TMOSFET are performed and simulated by using of the SILVACO TCAD 2D device simulator, Atlas. As a result, the specific on-state resistance of 1.2 mΩ-cm2 at the class of 100 V and 100 A is successfully optimized in the SJ TMOSFET, which has the better performance than TDMOS in design parameters. KCI Citation Count: 0 |
| Author | Clements, Mark A. Chung, Ikjoo |
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| Cites_doi | http://dx.doi.org/10.1109/97.700920 http://dx.doi.org/10.1109/LSP.2008.917803 http://dx.doi.org/10.1007/s11760-007-0011-x http://dx.doi.org/10.1016/S0165-1684(02)00247-5 http://dx.doi.org/10.1049/iet-spr:20070022 http://dx.doi.org/10.1049/iet-spr:20070217 http://dx.doi.org/10.1109/TSP.2002.806559 |
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| References_xml | – volume: 2 start-page: 431 issue: 4 year: 2008 end-page: 441 article-title: Robust Multichannel Least Mean Square‐Type Algorithms with Fast Decaying Transient for Blind Identification of Acoustic Channels publication-title: IET Signal Process. – volume: 51 start-page: 11 issue: 1 year: 2003 end-page: 24 article-title: A Class of Frequency‐Domain Adaptive Approaches to Blind Multichannel Identification publication-title: IEEE Trans. Signal Process. – volume: 1 start-page: 182 issue: 4 year: 2007 end-page: 189 article-title: Variable Step‐Size Multichannel Frequency‐Domain LMS Algorithm for Blind Identification of Finite Impulse Response Systems publication-title: IET Signal Process – volume: 82 start-page: 1127 issue: 8 year: 2002 end-page: 1138 article-title: Adaptive Multi‐channel Least Mean Square and Newton Algorithms for Blind Channel Identification publication-title: Signal Process. – volume: 1 start-page: 11 year: 2005 end-page: 14 article-title: Improving Robustness of Blind Adaptive Multichannel Identification Algorithms Using Constraints publication-title: Proc. European Signal Process. Conf. – volume: 1 start-page: 203 issue: 7 year: 2007 end-page: 213 article-title: Energy Constrained Frequency‐Domain Normalized LMS Algorithm for Blind Channel Identification publication-title: J. Signal, Image, Video Process. – volume: 5 start-page: 174 issue: 7 year: 1998 end-page: 176 article-title: On the Evaluation of Estimated Impulse Responses publication-title: IEEE Signal Process. Lett – volume: 15 start-page: 305 year: 2008 end-page: 308 article-title: Noise Robust Multichannel Frequency‐Domain LMS Algorithms for Blind Channel Identification publication-title: IEEE Signal Process. Lett. – ident: Key-10.4218/etrij.12.0211.0118-9 doi: http://dx.doi.org/10.1109/97.700920 – ident: Key-10.4218/etrij.12.0211.0118-6 doi: http://dx.doi.org/10.1109/LSP.2008.917803 – ident: Key-10.4218/etrij.12.0211.0118-8 doi: http://dx.doi.org/10.1007/s11760-007-0011-x – ident: Key-10.4218/etrij.12.0211.0118-1 doi: http://dx.doi.org/10.1016/S0165-1684(02)00247-5 – ident: Key-10.4218/etrij.12.0211.0118-4 doi: http://dx.doi.org/10.1049/iet-spr:20070022 – ident: Key-10.4218/etrij.12.0211.0118-5 doi: http://dx.doi.org/10.1049/iet-spr:20070217 – ident: Key-10.4218/etrij.12.0211.0118-2 doi: http://dx.doi.org/10.1109/TSP.2002.806559 |
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| SubjectTerms | Adaptive multichannel least‐mean‐square (LMS) algorithm blind channel identification (BCI) noise robust 전자/정보통신공학 |
| Title | Generalized Robust Multichannel Frequency‐Domain LMS Algorithms for Blind Channel Identification |
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