Low-Area and High-Throughput Architecture for an Adaptive Filter Using Distributed Arithmetic
A high-performance implementation scheme for a least mean square adaptive filter is presented. The architecture is based on distributed arithmetic in which the partial products of filter coefficients are precomputed and stored in lookup tables (LUTs) and the filtering is done by shift-and-accumulate...
Uložené v:
| Vydané v: | IEEE transactions on circuits and systems. II, Express briefs Ročník 60; číslo 11; s. 781 - 785 |
|---|---|
| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
New York
IEEE
01.11.2013
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Predmet: | |
| ISSN: | 1549-7747, 1558-3791 |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | A high-performance implementation scheme for a least mean square adaptive filter is presented. The architecture is based on distributed arithmetic in which the partial products of filter coefficients are precomputed and stored in lookup tables (LUTs) and the filtering is done by shift-and-accumulate operations on these partial products. In the case of an adaptive filter, it is required that the filter coefficients be updated and, hence, these LUTs are to be recalculated. A new strategy based on the offset binary coding scheme has been proposed in order to update these LUTs from time to time. Simulation results show that the proposed scheme consumes very less chip area and operates at high throughput for large base unit size k ( = N/m) , where m is an integer and N is the number of filter coefficients. For example, a 128-tap finite-impulse-response adaptive filter with the proposed implementation produces 12 times more throughput (for k = 8) and consumes almost 26% less area when compared to the best of existing architectures. |
|---|---|
| AbstractList | A high-performance implementation scheme for a least mean square adaptive filter is presented. The architecture is based on distributed arithmetic in which the partial products of filter coefficients are precomputed and stored in lookup tables (LUTs) and the filtering is done by shift-and-accumulate operations on these partial products. In the case of an adaptive filter, it is required that the filter coefficients be updated and, hence, these LUTs are to be recalculated. A new strategy based on the offset binary coding scheme has been proposed in order to update these LUTs from time to time. Simulation results show that the proposed scheme consumes very less chip area and operates at high throughput for large base unit size syntax error at token } , where m is an integer and N is the number of filter coefficients. For example, a 128-tap finite-impulse-response adaptive filter with the proposed implementation produces 12 times more throughput (for k = 8 ) and consumes almost 26% less area when compared to the best of existing architectures. A high-performance implementation scheme for a least mean square adaptive filter is presented. The architecture is based on distributed arithmetic in which the partial products of filter coefficients are precomputed and stored in lookup tables (LUTs) and the filtering is done by shift-and-accumulate operations on these partial products. In the case of an adaptive filter, it is required that the filter coefficients be updated and, hence, these LUTs are to be recalculated. A new strategy based on the offset binary coding scheme has been proposed in order to update these LUTs from time to time. Simulation results show that the proposed scheme consumes very less chip area and operates at high throughput for large base unit size [Formula Omitted], where [Formula Omitted] is an integer and [Formula Omitted] is the number of filter coefficients. For example, a 128-tap finite-impulse-response adaptive filter with the proposed implementation produces 12 times more throughput (for [Formula Omitted]) and consumes almost 26% less area when compared to the best of existing architectures. A high-performance implementation scheme for a least mean square adaptive filter is presented. The architecture is based on distributed arithmetic in which the partial products of filter coefficients are precomputed and stored in lookup tables (LUTs) and the filtering is done by shift-and-accumulate operations on these partial products. In the case of an adaptive filter, it is required that the filter coefficients be updated and, hence, these LUTs are to be recalculated. A new strategy based on the offset binary coding scheme has been proposed in order to update these LUTs from time to time. Simulation results show that the proposed scheme consumes very less chip area and operates at high throughput for large base unit size k ( = N/m) , where m is an integer and N is the number of filter coefficients. For example, a 128-tap finite-impulse-response adaptive filter with the proposed implementation produces 12 times more throughput (for k = 8) and consumes almost 26% less area when compared to the best of existing architectures. |
| Author | Prakash, M. Surya Shaik, Rafi Ahamed |
| Author_xml | – sequence: 1 givenname: M. Surya surname: Prakash fullname: Prakash, M. Surya organization: Indian Inst. of Technol. Guwahati, Guwahati, India – sequence: 2 givenname: Rafi Ahamed surname: Shaik fullname: Shaik, Rafi Ahamed organization: Indian Inst. of Technol. Guwahati, Guwahati, India |
| BookMark | eNp9kMFqGzEURUVJoUmaH2g3A910M66eNDOSlsZtGoMhizjLIGTNk0dhPHIlTUv_vnIdusiiIJAQ59z3uFfkYgoTEvIB6AKAqi_b1cN6vWAU-IIxCaIRb8gltK2suVBwcXo3qhbl_x25SumZUqYoZ5fkaRN-1cuIpjJTX935_VBvhxjm_XCcc7WMdvAZbZ4jVi7EAlXL3hyz_4nVrR8zxuox-WlfffUpR7-bM_bF8nk4YPb2PXnrzJjw5uW-Jo-337aru3pz_329Wm5qy5nMtRSOWoW9AaZ2rulRyI5h05TTc-ekZdR2bdfzRuzQ9tZYdC23jEHvQELLr8nnc-4xhh8zpqwPPlkcRzNhmJOGEgiqURIK-ukV-hzmOJXtNDStAt5RQQvFzpSNIaWITh-jP5j4WwPVp8b138b1qXH90niR5CvJ-myyD1OOxo__Vz-eVY-I_2Z1HYhOdPwPtBSRFQ |
| CODEN | ICSPE5 |
| CitedBy_id | crossref_primary_10_1007_s12046_022_02013_y crossref_primary_10_1007_s10772_020_09745_4 crossref_primary_10_1109_ACCESS_2023_3304234 crossref_primary_10_1177_0020720919833040 crossref_primary_10_1109_TCSI_2018_2867291 crossref_primary_10_1109_JETCAS_2017_2741499 crossref_primary_10_1049_iet_cds_2018_0041 crossref_primary_10_1109_TCSII_2020_3035693 crossref_primary_10_1016_j_neucom_2018_10_029 crossref_primary_10_1109_TCSI_2015_2437513 crossref_primary_10_1109_TCSI_2017_2725916 crossref_primary_10_1049_iet_spr_2014_0424 crossref_primary_10_1016_j_sigpro_2021_108083 crossref_primary_10_1007_s00034_015_0076_7 crossref_primary_10_1109_MCE_2020_2976418 crossref_primary_10_1109_TCSI_2014_2348072 crossref_primary_10_1002_cta_3467 crossref_primary_10_1049_iet_spr_2015_0446 crossref_primary_10_1109_ACCESS_2021_3083282 crossref_primary_10_1016_j_matpr_2020_12_869 crossref_primary_10_1109_TCSII_2022_3141687 crossref_primary_10_1109_TIM_2021_3132087 crossref_primary_10_1109_ACCESS_2022_3192619 crossref_primary_10_1007_s40031_024_01028_9 |
| Cites_doi | 10.1109/ACSSC.2011.6189976 10.1109/TASSP.1986.1164852 10.1109/TCSI.2005.851731 10.1049/ip-g-1.1986.0003 10.1109/TCSII.2011.2161168 10.1049/ip-f-1.1981.0040 10.1109/TASSP.1974.1162619 10.1109/ICASSP.2004.1327072 10.1109/53.29648 |
| ContentType | Journal Article |
| Copyright | Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Nov 2013 |
| Copyright_xml | – notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Nov 2013 |
| DBID | 97E RIA RIE AAYXX CITATION 7SP 8FD L7M F28 FR3 |
| DOI | 10.1109/TCSII.2013.2281747 |
| DatabaseName | IEEE All-Society Periodicals Package (ASPP) 2005–Present IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE/IET Electronic Library (IEL) (UW System Shared) CrossRef Electronics & Communications Abstracts Technology Research Database Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering Engineering Research Database |
| DatabaseTitle | CrossRef Technology Research Database Advanced Technologies Database with Aerospace Electronics & Communications Abstracts Engineering Research Database ANTE: Abstracts in New Technology & Engineering |
| DatabaseTitleList | Engineering Research Database Technology Research Database |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Xplore url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Architecture |
| EISSN | 1558-3791 |
| EndPage | 785 |
| ExternalDocumentID | 3128863791 10_1109_TCSII_2013_2281747 6617676 |
| Genre | orig-research |
| GroupedDBID | 0R~ 29I 4.4 5VS 6IK 6J9 97E AAJGR AARMG AASAJ AAWTH ABAZT ABQJQ ABVLG ACIWK AETIX AGQYO AGSQL AHBIQ AIBXA AKJIK AKQYR ALMA_UNASSIGNED_HOLDINGS ATWAV BEFXN BFFAM BGNUA BKEBE BPEOZ EBS EJD IFIPE IPLJI JAVBF M43 OCL PZZ RIA RIE RNS RXW TAE TAF VJK AAYXX CITATION 7SP 8FD L7M F28 FR3 |
| ID | FETCH-LOGICAL-c328t-87f0c9eda129bf4de7862e44e44d3ff8c20c656d347becdcacef53c221df18153 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 39 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000327251300013&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1549-7747 |
| IngestDate | Sun Sep 28 11:45:58 EDT 2025 Sun Nov 30 04:15:50 EST 2025 Sat Nov 29 02:22:58 EST 2025 Tue Nov 18 22:16:39 EST 2025 Tue Aug 26 16:47:26 EDT 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 11 |
| Language | English |
| License | https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c328t-87f0c9eda129bf4de7862e44e44d3ff8c20c656d347becdcacef53c221df18153 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| PQID | 1459136070 |
| PQPubID | 85412 |
| PageCount | 5 |
| ParticipantIDs | proquest_miscellaneous_1786194981 proquest_journals_1459136070 crossref_citationtrail_10_1109_TCSII_2013_2281747 ieee_primary_6617676 crossref_primary_10_1109_TCSII_2013_2281747 |
| PublicationCentury | 2000 |
| PublicationDate | 2013-11-01 |
| PublicationDateYYYYMMDD | 2013-11-01 |
| PublicationDate_xml | – month: 11 year: 2013 text: 2013-11-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationPlace | New York |
| PublicationPlace_xml | – name: New York |
| PublicationTitle | IEEE transactions on circuits and systems. II, Express briefs |
| PublicationTitleAbbrev | TCSII |
| PublicationYear | 2013 |
| Publisher | IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher_xml | – name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| References | ref12 surya prakash (ref13) 2012; 24 ref11 ref10 ref8 ref7 (ref2) 1973 parhi (ref5) 2007 ref9 ref4 ref3 ref6 haykin (ref1) 1996 |
| References_xml | – ident: ref12 doi: 10.1109/ACSSC.2011.6189976 – ident: ref8 doi: 10.1109/TASSP.1986.1164852 – year: 1996 ident: ref1 publication-title: Adaptive Filter Theory – ident: ref10 doi: 10.1109/TCSI.2005.851731 – ident: ref7 doi: 10.1049/ip-g-1.1986.0003 – ident: ref11 doi: 10.1109/TCSII.2011.2161168 – ident: ref6 doi: 10.1049/ip-f-1.1981.0040 – ident: ref3 doi: 10.1109/TASSP.1974.1162619 – ident: ref9 doi: 10.1109/ICASSP.2004.1327072 – ident: ref4 doi: 10.1109/53.29648 – year: 2007 ident: ref5 publication-title: VLSI Digital Signal Processing Systems Design and Implementation – volume: 24 start-page: 18 year: 2012 ident: ref13 article-title: High performance architecture for LMS based adaptive filter using distributed arithmetic publication-title: Proc ICICIC – year: 1973 ident: ref2 publication-title: Digital Filter for PCM Encoded Signals |
| SSID | ssj0029032 |
| Score | 2.2405248 |
| Snippet | A high-performance implementation scheme for a least mean square adaptive filter is presented. The architecture is based on distributed arithmetic in which the... |
| SourceID | proquest crossref ieee |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 781 |
| SubjectTerms | Adaptive filter Adaptive filters Architecture Arithmetic Clocks Consumption distributed arithmetic (DA) Filtering Filtration finite impulse response (FIR) Finite impulse response filters least mean square (LMS) Least mean squares algorithm Least squares approximations lookup table (LUT) Lookup tables offset binary coding (OBC) Registers Table lookup Throughput |
| Title | Low-Area and High-Throughput Architecture for an Adaptive Filter Using Distributed Arithmetic |
| URI | https://ieeexplore.ieee.org/document/6617676 https://www.proquest.com/docview/1459136070 https://www.proquest.com/docview/1786194981 |
| Volume | 60 |
| WOSCitedRecordID | wos000327251300013&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 Xplore customDbUrl: eissn: 1558-3791 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0029032 issn: 1549-7747 databaseCode: RIE dateStart: 20040101 isFulltext: true titleUrlDefault: https://ieeexplore.ieee.org/ providerName: IEEE |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3dS9xAEB9UfLAPWr2WnlrZQt80Z5LNZXcfj7OHByKFnnIvEnK7E3rQ5g7N6b_vzCYXFKVQyEMgs0mYyc78JvMF8N0VYR9RpwESWA64tDLQ-cwFRaojlEkira_wvr1S19d6OjU_N-CsrYVBRJ98hj0-9bF8t7Ar_lV2TrZEpSrdhE2l0rpWq3WuTOiHkXHHMUKMiVoXyITmfDL8NR5zFpfsxbEmCK5eGSE_VeWNKvb2ZbT3f2_2EXYbHCkGteD3YQPLA_jwortgB-6uFk_BgEChyEsnOKEjmNRTeZarSgxeRBAEIVciEgOXL1n9idGcg-jC5xOIC-6ty2Ox0NGqefX7Lxc-foKb0Y_J8DJopikEVsa6IrVXhNagy8nCc3YeKnJmMEnocLIotI1DS-DOyUSRXJ3NLRZ9aeM4cgXBgL78DFvlosQvIFJr0TjlNM8Qpw1vnHVO6ngWKRsWNu5CtGZvZptW4zzx4k_mXY7QZF4kGYska0TShdN2zbJutPFP6g4LoaVs-N-F47UUs2YvPpBz0zeRTEm3deFbe5l2EYdG8hIXK6IhZkQmMTo6fP_OR7DDz6-rEI9hq7pf4VfYto_V_OH-xH-Kzye23EE |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3da9RAEB9qFawPfrXF06or-KZpk91NdvfxqB49PA_BU_oiId2d4IHmjjan_74zm1yoKIKQh0BmwzKTnflN5gvgZajTHNEWCRJYTri0MrHVRUjqwmaotFY-Vnh_npn53J6fuw878HqohUHEmHyGx3wbY_lh5Tf8q-yEbIkpTHEDbuZay7Sr1hrcK5fGcWTcc4wwozbbEpnUnSxOP06nnMeljqW0BMLNb2YozlX5QxlHCzO59397uw93eyQpxp3oH8AONg_hzrX-gvvwZbb6mYwJFoqqCYJTOpJFN5dnvWnF-FoMQRB2JSIxDtWaFaCYLDmMLmJGgXjD3XV5MBYGWrVsv37n0scD-DR5uzg9S_p5ColX0rak-OrUOwwV2XjOz0ND7gxqTVdQdW29TD3Bu6C0IckGX3msc-WlzEJNQCBXh7DbrBp8BKLwHl0wwfIUcTryLvgQlJUXmfFp7eUIsi17S983G-eZF9_K6HSkrowiKVkkZS-SEbwa1qy7Vhv_pN5nIQyUPf9HcLSVYtmfxityb3KXqYK02wheDI_pHHFwpGpwtSEaYkbmtLPZ47-_-TncPlu8n5Wz6fzdE9jjvXQ1iUew215u8Cnc8j_a5dXls_hZ_gLCGN-I |
| 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=Low-Area+and+High-Throughput+Architecture+for+an+Adaptive+Filter+Using+Distributed+Arithmetic&rft.jtitle=IEEE+transactions+on+circuits+and+systems.+II%2C+Express+briefs&rft.au=Prakash%2C+MSurya&rft.au=Shaik%2C+Rafi+Ahamed&rft.date=2013-11-01&rft.issn=1549-7747&rft.eissn=1558-3791&rft.volume=60&rft.issue=11&rft.spage=781&rft.epage=785&rft_id=info:doi/10.1109%2FTCSII.2013.2281747&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1549-7747&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1549-7747&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1549-7747&client=summon |