Steady-State Behavior of General Complex-Valued Diffusion LMS Strategies
A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kanna, Sithan [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Übergeordnetes Werk: |
Enthalten in: IEEE signal processing letters - Institute of Electrical and Electronics Engineers ; ID: gnd/1692-5, New York, NY, 19XX, 23(2016), 5, Seite 722-726 |
|---|---|
| Übergeordnetes Werk: |
volume:23 ; year:2016 ; number:5 ; pages:722-726 |
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| DOI / URN: |
10.1109/LSP.2016.2547219 |
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| 520 | |a A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at all nodes. The proposed approach allows for the consideration of the second-order terms in the recursion for the weight error covariance matrix, without compromising the mathematical tractability of the problem. The closed form expressions for the mean square deviation (MSD) and excess mean square error (EMSE) for both the D-CLMS and D-ACLMS allow for the performance of the algorithms to be quantified as a function of the noncircularity of the input data. | ||
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| 650 | 4 | |a Covariance matrices | |
| 650 | 4 | |a augmented statistics | |
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| 650 | 4 | |a LMS | |
| 650 | 4 | |a Signal processing algorithms | |
| 650 | 4 | |a diffusion adaptation | |
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| 650 | 4 | |a Nickel | |
| 650 | 4 | |a Adaptive systems | |
| 650 | 4 | |a Steady-state | |
| 650 | 4 | |a Analytical models | |
| 700 | 1 | |a Mandic, Danilo P |4 oth | |
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10.1109/LSP.2016.2547219 doi PQ20160719 (DE-627)OLC197598773X (DE-599)GBVOLC197598773X (PRQ)i829-cf10abcc46cd55423fb924eb59d315b4dda4f78f2ba09fd0f041cd7c543a2fbe0 (KEY)02390256u20160000023000500722steadystatebehaviorofgeneralcomplexvalueddiffusion DE-627 ger DE-627 rakwb eng 53.00 bkl Kanna, Sithan verfasserin aut Steady-State Behavior of General Complex-Valued Diffusion LMS Strategies 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at all nodes. The proposed approach allows for the consideration of the second-order terms in the recursion for the weight error covariance matrix, without compromising the mathematical tractability of the problem. The closed form expressions for the mean square deviation (MSD) and excess mean square error (EMSE) for both the D-CLMS and D-ACLMS allow for the performance of the algorithms to be quantified as a function of the noncircularity of the input data. widely linear Covariance matrices augmented statistics Optimized production technology LMS Signal processing algorithms diffusion adaptation distributed optimisation Nickel Adaptive systems Steady-state Analytical models Mandic, Danilo P oth Enthalten in Institute of Electrical and Electronics Engineers ; ID: gnd/1692-5 IEEE signal processing letters New York, NY, 19XX 23(2016), 5, Seite 722-726 (DE-627)182273075 (DE-600)916964-7 1070-9908 nnns volume:23 year:2016 number:5 pages:722-726 http://dx.doi.org/10.1109/LSP.2016.2547219 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7442109 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT 53.00 AVZ AR 23 2016 5 722-726 |
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10.1109/LSP.2016.2547219 doi PQ20160719 (DE-627)OLC197598773X (DE-599)GBVOLC197598773X (PRQ)i829-cf10abcc46cd55423fb924eb59d315b4dda4f78f2ba09fd0f041cd7c543a2fbe0 (KEY)02390256u20160000023000500722steadystatebehaviorofgeneralcomplexvalueddiffusion DE-627 ger DE-627 rakwb eng 53.00 bkl Kanna, Sithan verfasserin aut Steady-State Behavior of General Complex-Valued Diffusion LMS Strategies 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at all nodes. The proposed approach allows for the consideration of the second-order terms in the recursion for the weight error covariance matrix, without compromising the mathematical tractability of the problem. The closed form expressions for the mean square deviation (MSD) and excess mean square error (EMSE) for both the D-CLMS and D-ACLMS allow for the performance of the algorithms to be quantified as a function of the noncircularity of the input data. widely linear Covariance matrices augmented statistics Optimized production technology LMS Signal processing algorithms diffusion adaptation distributed optimisation Nickel Adaptive systems Steady-state Analytical models Mandic, Danilo P oth Enthalten in Institute of Electrical and Electronics Engineers ; ID: gnd/1692-5 IEEE signal processing letters New York, NY, 19XX 23(2016), 5, Seite 722-726 (DE-627)182273075 (DE-600)916964-7 1070-9908 nnns volume:23 year:2016 number:5 pages:722-726 http://dx.doi.org/10.1109/LSP.2016.2547219 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7442109 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT 53.00 AVZ AR 23 2016 5 722-726 |
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10.1109/LSP.2016.2547219 doi PQ20160719 (DE-627)OLC197598773X (DE-599)GBVOLC197598773X (PRQ)i829-cf10abcc46cd55423fb924eb59d315b4dda4f78f2ba09fd0f041cd7c543a2fbe0 (KEY)02390256u20160000023000500722steadystatebehaviorofgeneralcomplexvalueddiffusion DE-627 ger DE-627 rakwb eng 53.00 bkl Kanna, Sithan verfasserin aut Steady-State Behavior of General Complex-Valued Diffusion LMS Strategies 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at all nodes. The proposed approach allows for the consideration of the second-order terms in the recursion for the weight error covariance matrix, without compromising the mathematical tractability of the problem. The closed form expressions for the mean square deviation (MSD) and excess mean square error (EMSE) for both the D-CLMS and D-ACLMS allow for the performance of the algorithms to be quantified as a function of the noncircularity of the input data. widely linear Covariance matrices augmented statistics Optimized production technology LMS Signal processing algorithms diffusion adaptation distributed optimisation Nickel Adaptive systems Steady-state Analytical models Mandic, Danilo P oth Enthalten in Institute of Electrical and Electronics Engineers ; ID: gnd/1692-5 IEEE signal processing letters New York, NY, 19XX 23(2016), 5, Seite 722-726 (DE-627)182273075 (DE-600)916964-7 1070-9908 nnns volume:23 year:2016 number:5 pages:722-726 http://dx.doi.org/10.1109/LSP.2016.2547219 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7442109 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT 53.00 AVZ AR 23 2016 5 722-726 |
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10.1109/LSP.2016.2547219 doi PQ20160719 (DE-627)OLC197598773X (DE-599)GBVOLC197598773X (PRQ)i829-cf10abcc46cd55423fb924eb59d315b4dda4f78f2ba09fd0f041cd7c543a2fbe0 (KEY)02390256u20160000023000500722steadystatebehaviorofgeneralcomplexvalueddiffusion DE-627 ger DE-627 rakwb eng 53.00 bkl Kanna, Sithan verfasserin aut Steady-State Behavior of General Complex-Valued Diffusion LMS Strategies 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at all nodes. The proposed approach allows for the consideration of the second-order terms in the recursion for the weight error covariance matrix, without compromising the mathematical tractability of the problem. The closed form expressions for the mean square deviation (MSD) and excess mean square error (EMSE) for both the D-CLMS and D-ACLMS allow for the performance of the algorithms to be quantified as a function of the noncircularity of the input data. widely linear Covariance matrices augmented statistics Optimized production technology LMS Signal processing algorithms diffusion adaptation distributed optimisation Nickel Adaptive systems Steady-state Analytical models Mandic, Danilo P oth Enthalten in Institute of Electrical and Electronics Engineers ; ID: gnd/1692-5 IEEE signal processing letters New York, NY, 19XX 23(2016), 5, Seite 722-726 (DE-627)182273075 (DE-600)916964-7 1070-9908 nnns volume:23 year:2016 number:5 pages:722-726 http://dx.doi.org/10.1109/LSP.2016.2547219 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7442109 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT 53.00 AVZ AR 23 2016 5 722-726 |
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Steady-State Behavior of General Complex-Valued Diffusion LMS Strategies |
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A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at all nodes. The proposed approach allows for the consideration of the second-order terms in the recursion for the weight error covariance matrix, without compromising the mathematical tractability of the problem. The closed form expressions for the mean square deviation (MSD) and excess mean square error (EMSE) for both the D-CLMS and D-ACLMS allow for the performance of the algorithms to be quantified as a function of the noncircularity of the input data. |
| abstractGer |
A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at all nodes. The proposed approach allows for the consideration of the second-order terms in the recursion for the weight error covariance matrix, without compromising the mathematical tractability of the problem. The closed form expressions for the mean square deviation (MSD) and excess mean square error (EMSE) for both the D-CLMS and D-ACLMS allow for the performance of the algorithms to be quantified as a function of the noncircularity of the input data. |
| abstract_unstemmed |
A novel methodology to bound the steady-state mean square performance of the diffusion complex least mean square (D-CLMS) and the diffusion widely linear (augmented) CLMS (D-ACLMS) algorithm is proposed. This is achieved by exploiting the almost identical nature of the steady-state filter weights at all nodes. The proposed approach allows for the consideration of the second-order terms in the recursion for the weight error covariance matrix, without compromising the mathematical tractability of the problem. The closed form expressions for the mean square deviation (MSD) and excess mean square error (EMSE) for both the D-CLMS and D-ACLMS allow for the performance of the algorithms to be quantified as a function of the noncircularity of the input data. |
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| title_short |
Steady-State Behavior of General Complex-Valued Diffusion LMS Strategies |
| url |
http://dx.doi.org/10.1109/LSP.2016.2547219 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7442109 |
| remote_bool |
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| author2 |
Mandic, Danilo P |
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| doi_str |
10.1109/LSP.2016.2547219 |
| up_date |
2024-07-03T14:18:18.680Z |
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1803567810406776832 |
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