An efficient robust adaptive filtering algorithm based on parallel subgradient projection techniques

This paper presents a novel robust adaptive filtering scheme based on the interactive use of statistical noise information and the ideas developed originally for efficient algorithmic solutions to the convex feasibility problems. The statistical noise information is quantitatively formulated as stoc...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on signal processing Jg. 50; H. 5; S. 1091 - 1101
Hauptverfasser:	Yamada, I., Slavakis, K., Yamada, K.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.05.2002 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive algorithm Adaptive filters Algorithms Applied sciences Computational efficiency Concurrent computing Convergence of numerical methods Detection, estimation, filtering, equalization, prediction Equations Exact sciences and technology Filtering algorithms Half spaces Information, signal and communications theory Inspection Linear equations Mathematical models Noise Noise robustness Projection Projection algorithms Signal and communications theory Signal, noise Stochastic resonance Studies Telecommunications and information theory Projection method Adaptive algorithm Adaptive filtering Parallel processing Signal processing Iterative method Set theory Adaptive estimation Gradient method Least mean squares methods
ISSN:	1053-587X, 1941-0476
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	This paper presents a novel robust adaptive filtering scheme based on the interactive use of statistical noise information and the ideas developed originally for efficient algorithmic solutions to the convex feasibility problems. The statistical noise information is quantitatively formulated as stochastic property closed convex sets by the simple design formulae developed in this paper. A simple set-theoretic inspection also leads to an important statistical reason for the sensitivity to noise of the affine projection algorithm (APA). The proposed adaptive algorithm is computationally efficient and robust to noise because it requires only an iterative parallel projection onto a series of closed half spaces that are highly expected to contain the unknown system to be identified and is free from the computational load of solving a system of linear equations. The numerical examples show that the proposed adaptive filtering scheme realizes dramatically fast and stable convergence for highly colored excited speech like input signals in severe noise situations.
AbstractList	This paper presents a novel robust adaptive filtering scheme based on the interactive use of statistical noise information and the ideas developed originally for efficient algorithmic solutions to the convex feasibility problems. The statistical noise information is quantitatively formulated as stochastic property closed convex sets by the simple design formulae developed in this paper. A simple set-theoretic inspection also leads to an important statistical reason for the sensitivity to noise of the affine projection algorithm (APA). The proposed adaptive algorithm is computationally efficient and robust to noise because it requires only an iterative parallel projection onto a series of closed half spaces that are highly expected to contain the unknown system to be identified and is free from the computational load of solving a system of linear equations. The numerical examples show that the proposed adaptive filtering scheme realizes dramatically fast and stable convergence for highly colored excited speech like input signals in severe noise situations. This paper presents a novel robust adaptive filtering scheme based on the interactive use of statistical noise information and the ideas developed originally for efficient algorithmic solutions to the convex feasibility problems. The statistical noise information is quantitatively formulated as stochastic property closed convex sets by the simple design formulae developed in this paper. A simple set-theoretic inspection also leads to an important statistical reason for the sensitivity to noise of the affine projection algorithm (APA). The proposed adaptive algorithm is computationally efficient and robust to noise because it requires only an iterative parallel projection onto a series of closed half spaces that are highly expected to contain the unknown system to be identified and is free from the computational load of solving a system of linear equations. The numerical examples show that the proposed adaptive filtering scheme realizes dramatically fast and stable convergence for highly colored excited speech like input signals in severe noise situations The proposed adaptive algorithm is computationally efficient and robust to noise because it requires only an iterative parallel projection onto a series of closed half spaces that are highly expected to contain the unknown system to be identified and is free from the computational load of solving a system of linear equations.
Author	Yamada, I. Slavakis, K. Yamada, K.
Author_xml	– sequence: 1 givenname: I. surname: Yamada fullname: Yamada, I. organization: Dept. of Commun. & Integrated Syst., Tokyo Inst. of Technol., Japan – sequence: 2 givenname: K. surname: Slavakis fullname: Slavakis, K. – sequence: 3 givenname: K. surname: Yamada fullname: Yamada, K.
BackLink	http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=13603351$$DView record in Pascal Francis
BookMark	eNqF0c9rHCEUB3ApCTQ_eui1Jym0oYdJ_DmOxxCaNhDoJYfe5I2jGxfX2aoT6H9fN7vkEEp7Unif99Wnp-gozckh9J6SS0qJvlLDpdaS9PINOqFa0I4I1R-1PZG8k4P6-RadlrImhAqh-xM0XSfsvA82uFRxnselVAwTbGt4ctiHWF0OaYUhruYc6uMGj1DchOeEt5AhRhdxWcZVhuk5YZvntbM1tHp19jGFX4sr5-jYQyzu3WE9Qw-3Xx9uvnf3P77d3Vzfd1YSVTtgVCtmFXDOuNfKCjFpbccJBEhvoR-ZsmyUarTKjsxr4JY6wQcmNSWcn6GLfWy7xO7YajahWBcjJDcvxWiitFa9Ek1-_qdkg6CEkv7_UMkWJ3aJH1_B9bzk1KY1wyC4poNgDX06ICgWos-QbChmm8MG8m9Ded-mkLS5q72zeS4lO29sqLB71JohREOJ2X22UYPZf3br-PKq4yX0L_bD3gbn3Is7FP8ApK-z_g
CODEN	ITPRED
CitedBy_id	crossref_primary_10_1002_eej_20369 crossref_primary_10_1016_j_automatica_2023_111501 crossref_primary_10_1007_s00034_024_02843_7 crossref_primary_10_1109_TNNLS_2011_2178321 crossref_primary_10_1016_j_automatica_2021_110059 crossref_primary_10_1109_LSP_2009_2027638 crossref_primary_10_1109_LSP_2016_2598615 crossref_primary_10_1109_TSP_2003_812846 crossref_primary_10_1587_transfun_E100_A_236 crossref_primary_10_1109_TSP_2006_881225 crossref_primary_10_4304_jnw_9_01_210_215 crossref_primary_10_1016_j_jmaa_2008_03_028 crossref_primary_10_1109_TSP_2018_2868040 crossref_primary_10_1016_j_aeue_2012_07_007 crossref_primary_10_1109_TSP_2015_2472365 crossref_primary_10_1137_100807004 crossref_primary_10_1109_TSP_2009_2018648 crossref_primary_10_1109_TSP_2023_3263255 crossref_primary_10_1109_TSP_2015_2437835 crossref_primary_10_1109_TSP_2009_2027397 crossref_primary_10_1002_acs_1237 crossref_primary_10_1016_j_compeleceng_2008_11_012 crossref_primary_10_1081_NFA_200045806 crossref_primary_10_1109_TCSII_2011_2158162 crossref_primary_10_1155_2008_735351 crossref_primary_10_1109_TNNLS_2013_2247626 crossref_primary_10_1109_TCNS_2023_3336833 crossref_primary_10_1109_TSP_2012_2200889 crossref_primary_10_1109_JSTSP_2007_910264 crossref_primary_10_1109_JSTSP_2011_2114325 crossref_primary_10_1080_01630560600884661 crossref_primary_10_1109_TSP_2013_2296881 crossref_primary_10_1109_TSP_2016_2563401 crossref_primary_10_1016_j_sigpro_2015_11_001 crossref_primary_10_4304_jnw_9_01_216_222 crossref_primary_10_1109_TSP_2007_893197 crossref_primary_10_1081_NFA_200045815 crossref_primary_10_1109_TSP_2008_917376 crossref_primary_10_1007_s11117_007_2066_x crossref_primary_10_1109_TSP_2009_2032450 crossref_primary_10_1007_s00034_010_9170_z crossref_primary_10_1109_TSP_2009_2020747 crossref_primary_10_1016_j_sigpro_2015_06_019 crossref_primary_10_1016_j_sigpro_2009_05_025 crossref_primary_10_1007_s10957_014_0659_7 crossref_primary_10_1109_TSP_2008_2009022 crossref_primary_10_1109_TSP_2018_2846271 crossref_primary_10_1109_TASL_2007_896655 crossref_primary_10_1109_TWC_2020_2969669 crossref_primary_10_1109_TSP_2009_2027771 crossref_primary_10_1007_s11228_006_0027_3 crossref_primary_10_1155_ASP_2006_84797 crossref_primary_10_1109_TSP_2007_907896 crossref_primary_10_1137_14096267X crossref_primary_10_1109_TSP_2010_2090874 crossref_primary_10_1109_TSP_2020_3029884 crossref_primary_10_1109_MSP_2010_938752 crossref_primary_10_1007_s11075_005_9010_6 crossref_primary_10_1109_LSP_2024_3402343 crossref_primary_10_1155_2009_589260 crossref_primary_10_1109_TASL_2008_916059 crossref_primary_10_1109_JSTSP_2013_2246766
Cites_doi	10.1109/78.205720 10.1109/78.485923 10.1016/0165-1684(96)00022-9 10.1007/BF02612715 10.1109/78.827542 10.1016/0041-5553(67)90113-9 10.1016/S1570-579X(01)80028-8 10.1109/83.563316 10.1109/ICASSP.2000.862007 10.1007/978-1-4757-6288-4 10.1109/5.214546 10.1109/TASSP.1980.1163432 10.1109/ICASSP.1995.479482 10.1109/78.533719 10.1016/S1570-579X(01)80003-3 10.1109/TASSP.1984.1164297 10.1109/89.736333 10.1080/01630569808816822 10.1137/S0036144593251710 10.1002/ecja.4400670503 10.1109/78.661344 10.1109/ICASSP.1996.543281 10.1109/TMI.1982.4307555 10.1109/TAC.1967.1098599 10.1109/TASSP.1984.1164334 10.1109/78.506609 10.1002/acs.4480090103 10.1109/78.134400
ContentType	Journal Article
Copyright	2002 INIST-CNRS Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2002
Copyright_xml	– notice: 2002 INIST-CNRS – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2002
DBID	RIA RIE AAYXX CITATION IQODW 7SC 7SP 8FD JQ2 L7M L~C L~D F28 FR3
DOI	10.1109/78.995065
DatabaseName	IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Pascal-Francis Computer and Information Systems Abstracts Electronics & Communications Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional ANTE: Abstracts in New Technology & Engineering Engineering Research Database
DatabaseTitle	CrossRef Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Professional Engineering Research Database ANTE: Abstracts in New Technology & Engineering
DatabaseTitleList	Technology Research Database Technology Research Database Technology Research Database Computer and Information Systems Abstracts
Database_xml	– sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Applied Sciences
EISSN	1941-0476
EndPage	1101
ExternalDocumentID	2430274521 13603351 10_1109_78_995065 995065
GroupedDBID	-~X .DC 0R~ 29I 3EH 4.4 53G 5GY 5VS 6IK 85S 97E AAJGR AARMG AASAJ AAWTH ABAZT ABFSI ABQJQ ABVLG ACGFO ACIWK ACKIV ACNCT AENEX AETIX AGQYO AGSQL AHBIQ AI. AIBXA AJQPL AKJIK AKQYR ALLEH ALMA_UNASSIGNED_HOLDINGS ASUFR ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ CS3 E.L EBS EJD F5P HZ~ H~9 ICLAB IFIPE IFJZH IPLJI JAVBF LAI MS~ O9- OCL P2P RIA RIE RNS TAE TN5 VH1 AAYXX CITATION AAYOK IQODW RIG 7SC 7SP 8FD JQ2 L7M L~C L~D F28 FR3
ID	FETCH-LOGICAL-c507t-a21972c7a3323f97c44d99cbda4a5fca6b27c2b57bc7cb2f9a3c1e4382591033
IEDL.DBID	RIE
ISICitedReferencesCount	104
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000174935200009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1053-587X
IngestDate	Sat Sep 27 17:05:15 EDT 2025 Sun Sep 28 05:24:34 EDT 2025 Sun Sep 28 01:35:15 EDT 2025 Sun Oct 05 00:27:39 EDT 2025 Wed Apr 02 07:17:11 EDT 2025 Sat Nov 29 08:07:21 EST 2025 Tue Nov 18 22:16:43 EST 2025 Tue Aug 26 16:34:44 EDT 2025
IsPeerReviewed	true
IsScholarly	true
Issue	5
Keywords	Projection method Adaptive algorithm Adaptive filtering Parallel processing Signal processing Iterative method Set theory Adaptive estimation Gradient method Least mean squares methods
Language	English
License	https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html CC BY 4.0
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c507t-a21972c7a3323f97c44d99cbda4a5fca6b27c2b57bc7cb2f9a3c1e4382591033
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 ObjectType-Article-2 ObjectType-Feature-1 content type line 23
PQID	884391842
PQPubID	23500
PageCount	11
ParticipantIDs	crossref_citationtrail_10_1109_78_995065 proquest_miscellaneous_28410106 proquest_journals_884391842 proquest_miscellaneous_27574344 proquest_miscellaneous_907997674 pascalfrancis_primary_13603351 ieee_primary_995065 crossref_primary_10_1109_78_995065
PublicationCentury	2000
PublicationDate	2002-05-01
PublicationDateYYYYMMDD	2002-05-01
PublicationDate_xml	– month: 05 year: 2002 text: 2002-05-01 day: 01
PublicationDecade	2000
PublicationPlace	New York, NY
PublicationPlace_xml	– name: New York, NY – name: New York
PublicationTitle	IEEE transactions on signal processing
PublicationTitleAbbrev	TSP
PublicationYear	2002
Publisher	IEEE Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: Institute of Electrical and Electronics Engineers – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref13 ref35 Yamada (ref38) 2000; 83 Bregman (ref39) 1965; 6 ref34 ref15 ref37 ref14 Golub (ref19) 1996 ref30 ref11 ref33 ref10 ref32 ref2 ref18 Nashed (ref40) 1976 Deutsch (ref36) 1998; 19 Porat (ref24) 1994 ref23 ref26 ref20 ref42 Kurosawa (ref31) 1988; 71-A ref41 Hinamoto (ref1) 1975; 95 ref22 ref21 ref43 Furukawa (ref3) 1988; 71-A ref27 Cramer (ref25) 1946 ref29 ref8 Luenberger (ref28) 1969 ref7 ref4 Censor (ref12) 1997 ref6 ref5 Haykin (ref9) 1996 Yamada (ref16) Stark (ref17) 1998
References_xml	– ident: ref10 doi: 10.1109/78.205720 – ident: ref41 doi: 10.1109/78.485923 – volume-title: Vector Space Projections-A Numerical Approach to Signal and Image Processing, Neural Nets, and Optics year: 1998 ident: ref17 – ident: ref42 doi: 10.1016/0165-1684(96)00022-9 – ident: ref15 doi: 10.1007/BF02612715 – volume: 19 start-page: 33 issue: 1 and 2 year: 1998 ident: ref36 article-title: Minimizing certain convex functions over the intersection of the fixed point sets of nonexpansive mappings publication-title: Numer. Funct. Anal. Optim – volume-title: Generalized Inverse and Applications year: 1976 ident: ref40 – ident: ref4 doi: 10.1109/78.827542 – ident: ref33 doi: 10.1016/0041-5553(67)90113-9 – ident: ref37 doi: 10.1016/S1570-579X(01)80028-8 – ident: ref14 doi: 10.1109/83.563316 – ident: ref6 doi: 10.1109/ICASSP.2000.862007 – volume: 83 start-page: 616 issue: 3 volume-title: J. IEICE year: 2000 ident: ref38 article-title: Convex projection algorithm from POCS to Hybrid steepest descent method – ident: ref23 doi: 10.1007/978-1-4757-6288-4 – ident: ref22 doi: 10.1109/5.214546 – ident: ref30 doi: 10.1109/TASSP.1980.1163432 – ident: ref5 doi: 10.1109/ICASSP.1995.479482 – ident: ref11 doi: 10.1109/78.533719 – ident: ref29 doi: 10.1016/S1570-579X(01)80003-3 – volume: 95 start-page: 227 issue: 10 volume-title: Trans. Inst. Elect. Eng. Jpn. year: 1975 ident: ref1 article-title: Extended theory of learning identifi-cation – volume-title: Proc. IEEE ICASSP ident: ref16 article-title: An efficient robust adaptive filtering scheme based on parallel sub gradient projection techniques – volume-title: Mathematical Methods of Statistics year: 1946 ident: ref25 – ident: ref26 doi: 10.1109/TASSP.1984.1164297 – ident: ref7 doi: 10.1109/89.736333 – ident: ref35 doi: 10.1080/01630569808816822 – ident: ref13 doi: 10.1137/S0036144593251710 – volume-title: Optimization by Vector Space Methods year: 1969 ident: ref28 – ident: ref2 doi: 10.1002/ecja.4400670503 – volume: 6 start-page: 688 year: 1965 ident: ref39 article-title: The method of successive projections for finding a common point of convex sets publication-title: Sov. Math. Dokl – ident: ref18 doi: 10.1109/78.661344 – ident: ref20 doi: 10.1109/ICASSP.1996.543281 – volume: 71-A start-page: 343 issue: 2 volume-title: IEICE Trans year: 1988 ident: ref31 article-title: A geometric interpretation of adaptive algorithms – ident: ref34 doi: 10.1109/TMI.1982.4307555 – ident: ref8 doi: 10.1109/TAC.1967.1098599 – ident: ref32 doi: 10.1109/TASSP.1984.1164334 – volume-title: Adaptive Filter Theory year: 1996 ident: ref9 – volume-title: Matrix Computations year: 1996 ident: ref19 – ident: ref43 doi: 10.1109/78.506609 – volume-title: Digital Processing of Random Sign a 1st Theory and Methods year: 1994 ident: ref24 – volume: 71-A start-page: 2138 issue: 12 volume-title: IEICE Trans year: 1988 ident: ref3 article-title: Orthogonal projection algorithm for block adaptive signal processing and some properties – ident: ref21 doi: 10.1002/acs.4480090103 – volume-title: Parallel Optimization: Theory, Algorithm, and Optimization year: 1997 ident: ref12 – ident: ref27 doi: 10.1109/78.134400
SSID	ssj0014496
Score	2.0991192
Snippet	This paper presents a novel robust adaptive filtering scheme based on the interactive use of statistical noise information and the ideas developed originally... The proposed adaptive algorithm is computationally efficient and robust to noise because it requires only an iterative parallel projection onto a series of...
SourceID	proquest pascalfrancis crossref ieee
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	1091
SubjectTerms	Adaptive algorithm Adaptive filters Algorithms Applied sciences Computational efficiency Concurrent computing Convergence of numerical methods Detection, estimation, filtering, equalization, prediction Equations Exact sciences and technology Filtering algorithms Half spaces Information, signal and communications theory Inspection Linear equations Mathematical models Noise Noise robustness Projection Projection algorithms Signal and communications theory Signal, noise Stochastic resonance Studies Telecommunications and information theory
Title	An efficient robust adaptive filtering algorithm based on parallel subgradient projection techniques
URI	https://ieeexplore.ieee.org/document/995065 https://www.proquest.com/docview/884391842 https://www.proquest.com/docview/27574344 https://www.proquest.com/docview/28410106 https://www.proquest.com/docview/907997674
Volume	50
WOSCitedRecordID	wos000174935200009&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVIEE databaseName: IEEE Electronic Library (IEL) customDbUrl: eissn: 1941-0476 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0014496 issn: 1053-587X databaseCode: RIE dateStart: 19910101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB7RigMceBRQQ6FYiAOXtBs_YvtYISpOFYce9hbZY6esFJIqD34_tpMNVBQkblEylkae2DPjGX8fwAejpPUhLMipMTrnrixzSzcmL4xC9E6I0qtENiGvrtR2q78uONvpLoz3PjWf-bP4mGr5rsMpHpWday2CxzyAAynL-arWWjDgPFFxhWiB5ULJ7QIiVGz0uVRn88A7ridxqcROSDOEyahnFos_NuTkZS6f_pd-z-DJEkySi9n6z-GBb4_g8W8Qgy_AXbTEJ5iIMJT0nZ2GkRhnbuM2R-pdLJYHQWKam67fjd--k-jXHOlaElHBm8Y3ZJjsTZ9aw0aynNwEa5IV_nV4CdeXn68_fckXZoUcQ_w35oZGtjGUhjHKai2Rc6c1Wme4ETWa0lKJ1AppUaKltTYMCx9rhiKEF4y9gsO2a_0xEIdKcc_1xtbIDXNKhrS0LpjzFmktMIOP-zmvcEEdj-QXTZWyj42upKrmecvg_Sp6O0Nt3Cd0FOd9Fdi_Pb1jx1_jWRnUFUUGJ3vDVssiHaqgOdMhw6UZvFu_htUVSyam9d00VFSKEGJx_g8JxYuYV2dA_iKhN1LriJn0-l7dT-BRYphJTZRv4HDsJ_8WHuKPcTf0p-kv_wmZaP-k
linkProvider	IEEE
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwEB5BQQIOPAqIUGgtxIFL2sSP2D5WiKqIsuKwh71FfqVdKSRVHvx-bCcbqChI3KJkLI08sWfGM_4-gPdKcO18WJBipWRKbVGkGmcqzZUwxlnGCici2QRfrcRmI7_NONvxLoxzLjafuePwGGv5tjVjOCo7kZJ5j3kX7jFKcTZd1lpKBpRGMi4fL5CUCb6ZYYTyTJ5wcTwNveF8IptK6IVUvZ-OauKx-GNLjn7m7Ml_afgUHs_hJDqd7P8M7rhmHx79BjL4HOxpg1wEivBDUdfqsR-Qsuo6bHSo2oZyuRdEqr5su-1w9R0Fz2ZR26CAC17Xrkb9qC-72Bw2oPnsxtsTLQCw_QtYn31afzxPZ26F1PgIcEgVDnxjhitCMKkkN5RaKY22iipWGVVozA3WjGvDjcaVVMTkLlQNmQ8wCHkJe03buFeArBGCOiozXRmqiBXcJ6ZVTqzTBlfMJPBhN-elmXHHA_1FXcb8I5MlF-U0bwm8W0SvJ7CN24T2w7wvAru3hzfs-Gs8Kby6LE_gYGfYcl6mfek1J9LnuDiBo-WrX1-haKIa1459iTnzQRal_5AQNA-ZdQLoLxIy41IG1KTXt-p-BA_O118vyovPqy8H8DDyzcSWyjewN3Sjewv3zY9h23eH8Y__Cf4pAvo
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=An+efficient+robust+adaptive+filtering+algorithm+based+on+parallel+subgradient+projection+techniques&rft.jtitle=IEEE+transactions+on+signal+processing&rft.au=Yamada%2C+I.&rft.au=Slavakis%2C+K.&rft.au=Yamada%2C+K.&rft.date=2002-05-01&rft.pub=IEEE&rft.issn=1053-587X&rft.volume=50&rft.issue=5&rft.spage=1091&rft.epage=1101&rft_id=info:doi/10.1109%2F78.995065&rft.externalDocID=995065
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1053-587X&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1053-587X&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1053-587X&client=summon