Tracking analysis of augmented complex least mean square algorithm
The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Khalili, Azam [verfasserIn] |
|---|
| Format: |
Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
|---|
| Rechteinformationen: |
Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. |
|---|
| Schlagwörter: |
|---|
| Übergeordnetes Werk: |
Enthalten in: International journal of adaptive control and signal processing - Chichester, Sussex [u.a.] : Wiley, 1987, 30(2016), 1, Seite 106-114 |
|---|---|
| Übergeordnetes Werk: |
volume:30 ; year:2016 ; number:1 ; pages:106-114 |
| Links: |
|---|
| DOI / URN: |
10.1002/acs.2594 |
|---|
| Katalog-ID: |
OLC195782980X |
|---|
| LEADER | 01000caa a2200265 4500 | ||
|---|---|---|---|
| 001 | OLC195782980X | ||
| 003 | DE-627 | ||
| 005 | 20220216064851.0 | ||
| 007 | tu | ||
| 008 | 160206s2016 xx ||||| 00| ||eng c | ||
| 024 | 7 | |a 10.1002/acs.2594 |2 doi | |
| 028 | 5 | 2 | |a PQ20160617 |
| 035 | |a (DE-627)OLC195782980X | ||
| 035 | |a (DE-599)GBVOLC195782980X | ||
| 035 | |a (PRQ)c1524-abec90a5d163734ae32e35f4c8b659447c579bc7d802fcca9c79590a86014d9a3 | ||
| 035 | |a (KEY)0163452620160000030000100106trackinganalysisofaugmentedcomplexleastmeansquarea | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 082 | 0 | 4 | |a 600 |q ZDB |
| 084 | |a 50.23 |2 bkl | ||
| 084 | |a 53.73 |2 bkl | ||
| 100 | 1 | |a Khalili, Azam |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Tracking analysis of augmented complex least mean square algorithm |
| 264 | 1 | |c 2016 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
| 338 | |a Band |b nc |2 rdacarrier | ||
| 520 | |a The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd. | ||
| 540 | |a Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. | ||
| 650 | 4 | |a energy conservation | |
| 650 | 4 | |a tracking | |
| 650 | 4 | |a widely linear model | |
| 650 | 4 | |a augmented CLMS | |
| 700 | 1 | |a Rastegarnia, Amir |4 oth | |
| 773 | 0 | 8 | |i Enthalten in |t International journal of adaptive control and signal processing |d Chichester, Sussex [u.a.] : Wiley, 1987 |g 30(2016), 1, Seite 106-114 |w (DE-627)129242489 |w (DE-600)58715-1 |w (DE-576)018613578 |x 0890-6327 |7 nnns |
| 773 | 1 | 8 | |g volume:30 |g year:2016 |g number:1 |g pages:106-114 |
| 856 | 4 | 1 | |u http://dx.doi.org/10.1002/acs.2594 |3 Volltext |
| 856 | 4 | 2 | |u http://onlinelibrary.wiley.com/doi/10.1002/acs.2594/abstract |
| 856 | 4 | 2 | |u http://search.proquest.com/docview/1753349769 |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a SYSFLAG_A | ||
| 912 | |a GBV_OLC | ||
| 912 | |a SSG-OLC-TEC | ||
| 912 | |a SSG-OLC-MAT | ||
| 912 | |a GBV_ILN_70 | ||
| 936 | b | k | |a 50.23 |q AVZ |
| 936 | b | k | |a 53.73 |q AVZ |
| 951 | |a AR | ||
| 952 | |d 30 |j 2016 |e 1 |h 106-114 | ||
| author_variant |
a k ak |
|---|---|
| matchkey_str |
article:08906327:2016----::rcignlssfumnecmlxesma |
| hierarchy_sort_str |
2016 |
| bklnumber |
50.23 53.73 |
| publishDate |
2016 |
| allfields |
10.1002/acs.2594 doi PQ20160617 (DE-627)OLC195782980X (DE-599)GBVOLC195782980X (PRQ)c1524-abec90a5d163734ae32e35f4c8b659447c579bc7d802fcca9c79590a86014d9a3 (KEY)0163452620160000030000100106trackinganalysisofaugmentedcomplexleastmeansquarea DE-627 ger DE-627 rakwb eng 600 ZDB 50.23 bkl 53.73 bkl Khalili, Azam verfasserin aut Tracking analysis of augmented complex least mean square algorithm 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. energy conservation tracking widely linear model augmented CLMS Rastegarnia, Amir oth Enthalten in International journal of adaptive control and signal processing Chichester, Sussex [u.a.] : Wiley, 1987 30(2016), 1, Seite 106-114 (DE-627)129242489 (DE-600)58715-1 (DE-576)018613578 0890-6327 nnns volume:30 year:2016 number:1 pages:106-114 http://dx.doi.org/10.1002/acs.2594 Volltext http://onlinelibrary.wiley.com/doi/10.1002/acs.2594/abstract http://search.proquest.com/docview/1753349769 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 50.23 AVZ 53.73 AVZ AR 30 2016 1 106-114 |
| spelling |
10.1002/acs.2594 doi PQ20160617 (DE-627)OLC195782980X (DE-599)GBVOLC195782980X (PRQ)c1524-abec90a5d163734ae32e35f4c8b659447c579bc7d802fcca9c79590a86014d9a3 (KEY)0163452620160000030000100106trackinganalysisofaugmentedcomplexleastmeansquarea DE-627 ger DE-627 rakwb eng 600 ZDB 50.23 bkl 53.73 bkl Khalili, Azam verfasserin aut Tracking analysis of augmented complex least mean square algorithm 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. energy conservation tracking widely linear model augmented CLMS Rastegarnia, Amir oth Enthalten in International journal of adaptive control and signal processing Chichester, Sussex [u.a.] : Wiley, 1987 30(2016), 1, Seite 106-114 (DE-627)129242489 (DE-600)58715-1 (DE-576)018613578 0890-6327 nnns volume:30 year:2016 number:1 pages:106-114 http://dx.doi.org/10.1002/acs.2594 Volltext http://onlinelibrary.wiley.com/doi/10.1002/acs.2594/abstract http://search.proquest.com/docview/1753349769 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 50.23 AVZ 53.73 AVZ AR 30 2016 1 106-114 |
| allfields_unstemmed |
10.1002/acs.2594 doi PQ20160617 (DE-627)OLC195782980X (DE-599)GBVOLC195782980X (PRQ)c1524-abec90a5d163734ae32e35f4c8b659447c579bc7d802fcca9c79590a86014d9a3 (KEY)0163452620160000030000100106trackinganalysisofaugmentedcomplexleastmeansquarea DE-627 ger DE-627 rakwb eng 600 ZDB 50.23 bkl 53.73 bkl Khalili, Azam verfasserin aut Tracking analysis of augmented complex least mean square algorithm 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. energy conservation tracking widely linear model augmented CLMS Rastegarnia, Amir oth Enthalten in International journal of adaptive control and signal processing Chichester, Sussex [u.a.] : Wiley, 1987 30(2016), 1, Seite 106-114 (DE-627)129242489 (DE-600)58715-1 (DE-576)018613578 0890-6327 nnns volume:30 year:2016 number:1 pages:106-114 http://dx.doi.org/10.1002/acs.2594 Volltext http://onlinelibrary.wiley.com/doi/10.1002/acs.2594/abstract http://search.proquest.com/docview/1753349769 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 50.23 AVZ 53.73 AVZ AR 30 2016 1 106-114 |
| allfieldsGer |
10.1002/acs.2594 doi PQ20160617 (DE-627)OLC195782980X (DE-599)GBVOLC195782980X (PRQ)c1524-abec90a5d163734ae32e35f4c8b659447c579bc7d802fcca9c79590a86014d9a3 (KEY)0163452620160000030000100106trackinganalysisofaugmentedcomplexleastmeansquarea DE-627 ger DE-627 rakwb eng 600 ZDB 50.23 bkl 53.73 bkl Khalili, Azam verfasserin aut Tracking analysis of augmented complex least mean square algorithm 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. energy conservation tracking widely linear model augmented CLMS Rastegarnia, Amir oth Enthalten in International journal of adaptive control and signal processing Chichester, Sussex [u.a.] : Wiley, 1987 30(2016), 1, Seite 106-114 (DE-627)129242489 (DE-600)58715-1 (DE-576)018613578 0890-6327 nnns volume:30 year:2016 number:1 pages:106-114 http://dx.doi.org/10.1002/acs.2594 Volltext http://onlinelibrary.wiley.com/doi/10.1002/acs.2594/abstract http://search.proquest.com/docview/1753349769 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 50.23 AVZ 53.73 AVZ AR 30 2016 1 106-114 |
| allfieldsSound |
10.1002/acs.2594 doi PQ20160617 (DE-627)OLC195782980X (DE-599)GBVOLC195782980X (PRQ)c1524-abec90a5d163734ae32e35f4c8b659447c579bc7d802fcca9c79590a86014d9a3 (KEY)0163452620160000030000100106trackinganalysisofaugmentedcomplexleastmeansquarea DE-627 ger DE-627 rakwb eng 600 ZDB 50.23 bkl 53.73 bkl Khalili, Azam verfasserin aut Tracking analysis of augmented complex least mean square algorithm 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd. Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd. energy conservation tracking widely linear model augmented CLMS Rastegarnia, Amir oth Enthalten in International journal of adaptive control and signal processing Chichester, Sussex [u.a.] : Wiley, 1987 30(2016), 1, Seite 106-114 (DE-627)129242489 (DE-600)58715-1 (DE-576)018613578 0890-6327 nnns volume:30 year:2016 number:1 pages:106-114 http://dx.doi.org/10.1002/acs.2594 Volltext http://onlinelibrary.wiley.com/doi/10.1002/acs.2594/abstract http://search.proquest.com/docview/1753349769 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 50.23 AVZ 53.73 AVZ AR 30 2016 1 106-114 |
| language |
English |
| source |
Enthalten in International journal of adaptive control and signal processing 30(2016), 1, Seite 106-114 volume:30 year:2016 number:1 pages:106-114 |
| sourceStr |
Enthalten in International journal of adaptive control and signal processing 30(2016), 1, Seite 106-114 volume:30 year:2016 number:1 pages:106-114 |
| format_phy_str_mv |
Article |
| institution |
findex.gbv.de |
| topic_facet |
energy conservation tracking widely linear model augmented CLMS |
| dewey-raw |
600 |
| isfreeaccess_bool |
false |
| container_title |
International journal of adaptive control and signal processing |
| authorswithroles_txt_mv |
Khalili, Azam @@aut@@ Rastegarnia, Amir @@oth@@ |
| publishDateDaySort_date |
2016-01-01T00:00:00Z |
| hierarchy_top_id |
129242489 |
| dewey-sort |
3600 |
| id |
OLC195782980X |
| language_de |
englisch |
| fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC195782980X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220216064851.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160206s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/acs.2594</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160617</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC195782980X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC195782980X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c1524-abec90a5d163734ae32e35f4c8b659447c579bc7d802fcca9c79590a86014d9a3</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0163452620160000030000100106trackinganalysisofaugmentedcomplexleastmeansquarea</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">ZDB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.23</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">53.73</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Khalili, Azam</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Tracking analysis of augmented complex least mean square algorithm</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">energy conservation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">tracking</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">widely linear model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">augmented CLMS</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rastegarnia, Amir</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">International journal of adaptive control and signal processing</subfield><subfield code="d">Chichester, Sussex [u.a.] : Wiley, 1987</subfield><subfield code="g">30(2016), 1, Seite 106-114</subfield><subfield code="w">(DE-627)129242489</subfield><subfield code="w">(DE-600)58715-1</subfield><subfield code="w">(DE-576)018613578</subfield><subfield code="x">0890-6327</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:30</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:106-114</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1002/acs.2594</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1002/acs.2594/abstract</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1753349769</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">50.23</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">53.73</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">30</subfield><subfield code="j">2016</subfield><subfield code="e">1</subfield><subfield code="h">106-114</subfield></datafield></record></collection>
|
| author |
Khalili, Azam |
| spellingShingle |
Khalili, Azam ddc 600 bkl 50.23 bkl 53.73 misc energy conservation misc tracking misc widely linear model misc augmented CLMS Tracking analysis of augmented complex least mean square algorithm |
| authorStr |
Khalili, Azam |
| ppnlink_with_tag_str_mv |
@@773@@(DE-627)129242489 |
| format |
Article |
| dewey-ones |
600 - Technology |
| delete_txt_mv |
keep |
| author_role |
aut |
| collection |
OLC |
| remote_str |
false |
| illustrated |
Not Illustrated |
| issn |
0890-6327 |
| topic_title |
600 ZDB 50.23 bkl 53.73 bkl Tracking analysis of augmented complex least mean square algorithm energy conservation tracking widely linear model augmented CLMS |
| topic |
ddc 600 bkl 50.23 bkl 53.73 misc energy conservation misc tracking misc widely linear model misc augmented CLMS |
| topic_unstemmed |
ddc 600 bkl 50.23 bkl 53.73 misc energy conservation misc tracking misc widely linear model misc augmented CLMS |
| topic_browse |
ddc 600 bkl 50.23 bkl 53.73 misc energy conservation misc tracking misc widely linear model misc augmented CLMS |
| format_facet |
Aufsätze Gedruckte Aufsätze |
| format_main_str_mv |
Text Zeitschrift/Artikel |
| carriertype_str_mv |
nc |
| author2_variant |
a r ar |
| hierarchy_parent_title |
International journal of adaptive control and signal processing |
| hierarchy_parent_id |
129242489 |
| dewey-tens |
600 - Technology |
| hierarchy_top_title |
International journal of adaptive control and signal processing |
| isfreeaccess_txt |
false |
| familylinks_str_mv |
(DE-627)129242489 (DE-600)58715-1 (DE-576)018613578 |
| title |
Tracking analysis of augmented complex least mean square algorithm |
| ctrlnum |
(DE-627)OLC195782980X (DE-599)GBVOLC195782980X (PRQ)c1524-abec90a5d163734ae32e35f4c8b659447c579bc7d802fcca9c79590a86014d9a3 (KEY)0163452620160000030000100106trackinganalysisofaugmentedcomplexleastmeansquarea |
| title_full |
Tracking analysis of augmented complex least mean square algorithm |
| author_sort |
Khalili, Azam |
| journal |
International journal of adaptive control and signal processing |
| journalStr |
International journal of adaptive control and signal processing |
| lang_code |
eng |
| isOA_bool |
false |
| dewey-hundreds |
600 - Technology |
| recordtype |
marc |
| publishDateSort |
2016 |
| contenttype_str_mv |
txt |
| container_start_page |
106 |
| author_browse |
Khalili, Azam |
| container_volume |
30 |
| class |
600 ZDB 50.23 bkl 53.73 bkl |
| format_se |
Aufsätze |
| author-letter |
Khalili, Azam |
| doi_str_mv |
10.1002/acs.2594 |
| dewey-full |
600 |
| title_sort |
tracking analysis of augmented complex least mean square algorithm |
| title_auth |
Tracking analysis of augmented complex least mean square algorithm |
| abstract |
The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd. |
| abstractGer |
The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd. |
| abstract_unstemmed |
The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd. |
| collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 |
| container_issue |
1 |
| title_short |
Tracking analysis of augmented complex least mean square algorithm |
| url |
http://dx.doi.org/10.1002/acs.2594 http://onlinelibrary.wiley.com/doi/10.1002/acs.2594/abstract http://search.proquest.com/docview/1753349769 |
| remote_bool |
false |
| author2 |
Rastegarnia, Amir |
| author2Str |
Rastegarnia, Amir |
| ppnlink |
129242489 |
| mediatype_str_mv |
n |
| isOA_txt |
false |
| hochschulschrift_bool |
false |
| author2_role |
oth |
| doi_str |
10.1002/acs.2594 |
| up_date |
2024-07-04T01:29:30.063Z |
| _version_ |
1803610038010380288 |
| fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC195782980X</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220216064851.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160206s2016 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/acs.2594</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160617</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC195782980X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC195782980X</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c1524-abec90a5d163734ae32e35f4c8b659447c579bc7d802fcca9c79590a86014d9a3</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0163452620160000030000100106trackinganalysisofaugmentedcomplexleastmeansquarea</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">600</subfield><subfield code="q">ZDB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.23</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">53.73</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Khalili, Azam</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Tracking analysis of augmented complex least mean square algorithm</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2016</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The augmented complex least mean‐square (ACLMS) algorithm is a suitable algorithm for the processing of both second‐order circular (proper) and noncircular (improper) signals. In this paper, we provide tracking analysis of the ACLMS algorithm in the non‐stationary environments. Using the established energy conservation argument, we derive a variance relation that contains moments that represent the effects of non‐stationary environment. We evaluate these moments and derive closed‐form expressions for the excess mean‐square error (EMSE) and mean‐square error (MSE). The derived expressions, supported by simulations, reveal that unlike the stationary case, the steady‐state EMSE, and MSE curves are not monotonically increasing functions of the step‐size parameter. We also use this observation to optimize the step‐size learning parameter. Simulation results illustrate the theoretical findings and match well with theory. Copyright © 2015 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: Copyright © 2015 John Wiley & Sons, Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">energy conservation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">tracking</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">widely linear model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">augmented CLMS</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rastegarnia, Amir</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">International journal of adaptive control and signal processing</subfield><subfield code="d">Chichester, Sussex [u.a.] : Wiley, 1987</subfield><subfield code="g">30(2016), 1, Seite 106-114</subfield><subfield code="w">(DE-627)129242489</subfield><subfield code="w">(DE-600)58715-1</subfield><subfield code="w">(DE-576)018613578</subfield><subfield code="x">0890-6327</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:30</subfield><subfield code="g">year:2016</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:106-114</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1002/acs.2594</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1002/acs.2594/abstract</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1753349769</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">50.23</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">53.73</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">30</subfield><subfield code="j">2016</subfield><subfield code="e">1</subfield><subfield code="h">106-114</subfield></datafield></record></collection>
|
| score |
7.3998623 |