6
社団法人電子情報通信学会 THEINSTITUTEOFELECTRONICS, INFORMATIONANDCOⅦUNICATIONENGINEERS 信学技報 TECHNICALREPORTOFIEICE・ Cs96-138,IE96-lO7(1996-12) バックプロパゲーション適応IIRフィルタのための 2次元LMSアルゴリズムの収束性に関する検討 マハシャダイデ 川又政征 東北大学大学院工学研究科 〒980-77仙台市青葉区荒巻字青葉 E-majl:maha@mk・ecei,tohoku・acjp あらまし 本稿では,‘誤差方程式に基づく,バックプロパゲーション適応ⅡRフィルタのための2次元LMS アルゴリズムを提案し,リヤプノフ安定定理を用いて,このアルゴリズムの収束性を考察する.とくに,分母分 離形2次元IIRフィルタのために適応アルゴリズムを提案し,収束性を考察する.このアルゴリズムでは,フィル タの分母の水平セクションと垂直セクションの縦続結合に望ましい信号がバックプロパゲーションされることに より,フィルタの係数に関してウ線形な中間誤差関数を生成する.提案したアルゴリズムの性能を明らかにするた めシミュレーション結果を示す.しかし,望ましい信号が加法ノイズに乱されている場合は,推定値のバイアス誤 差が多いという問題点がある.そのバイアス誤差を無くすための方法を提案し,シミュレーション結果を示す. キーワード2次元誤差方程式適応IIRフィルタ,分母分離形2次元バックプロパゲーションIIRフィルタ. OntheConvergenceof2-DLMSAlgorithm fbrBackpropagationAdaptivellRFilters MahaSHADAYDEHandMasayllkiKAWAMArA GraduateSchoolofEngineering,nhokuUniver8ity AOba,Aramnaki,AobaFku、Sendaj980-77,Japan E-majl:maha@mk,ccei、tohoku、acjp Abstract Thispaperdevelopsa2-Dextensionofthel-Dstabilitytheoryapproachtoequationerroradaptive lIRfilters・Thenanalgorithmbasedontheb誠kpropagationfbrmulationof2-DequationerroradaptivelIR filterswithseparabledenominatorfunctionisproposedanditsconvegenceanalysisisconsidered・Thisalgorithm isbasedontheconceptofb“kpropagatingthedesiredsignajthroughacascadeofthedenominatorvertica1and horizontalpartssothattWolinearerrorfimctionscanbegenerated・Simulationresults麺epresentedtoshow thattheproposeda1gorithmconvergestotheoptima1solutionwhenthedesiredsignalisfreefromadditive nmse-However,ifthedesiredsignaliscontaminatedwithadditivenoise,theproposedalgorithmresultsin biasedestimates・Andthus,abiasremowJmethodanditssimulationresultsarepresented・ keywords 2,equationerroradaptivellRfilter,separabledenominatorbackpropagationllR・filter. -61-

OntheConvergenceof2-DLMSAlgorithm …像2(、,”)麺eline麺withrespecttotheupd孔tedpa戸 rameters麺ldhG1M9ewithgood《9hoi《9eofthestepsize,Eqs.(24)and(29)willconv燈rgetothegloMminimum

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Page 1: OntheConvergenceof2-DLMSAlgorithm …像2(、,”)麺eline麺withrespecttotheupd孔tedpa戸 rameters麺ldhG1M9ewithgood《9hoi《9eofthestepsize,Eqs.(24)and(29)willconv燈rgetothegloMminimum

社団法人電子情報通信学会THEINSTITUTEOFELECTRONICS,INFORMATIONANDCOⅦUNICATIONENGINEERS

信学技報TECHNICALREPORTOFIEICE・

Cs96-138,IE96-lO7(1996-12)

バックプロパゲーション適応IIRフィルタのための

2次元LMSアルゴリズムの収束性に関する検討

マハシャダイデ 川又政征

東北大学大学院工学研究科

〒980-77仙台市青葉区荒巻字青葉

E-majl:maha@mk・ecei,tohoku・acjp

あら まし 本稿では,‘誤差方程式に基づく,バックプロパゲーション適応ⅡRフィルタのための2次元LMS

アルゴリズムを提案し,リヤプノフ安定定理を用いて,このアルゴリズムの収束性を考察する.とくに,分母分

離形2次元IIRフィルタのために適応アルゴリズムを提案し,収束性を考察する.このアルゴリズムでは,フィル

タの分母の水平セクションと垂直セクションの縦続結合に望ましい信号がバックプロパゲーションされることに

より,フィルタの係数に関してウ線形な中間誤差関数を生成する.提案したアルゴリズムの性能を明らかにするた

めシミュレーション結果を示す.しかし,望ましい信号が加法ノイズに乱されている場合は,推定値のバイアス誤

差が多いという問題点がある.そのバイアス誤差を無くすための方法を提案し,シミュレーション結果を示す.

キーワード2次元誤差方程式適応IIRフィルタ,分母分離形2次元バックプロパゲーションIIRフィルタ.

OntheConvergenceof2-DLMSAlgorithm

fbrBackpropagationAdaptivellRFilters

MahaSHADAYDEHandMasayllkiKAWAMArA

GraduateSchoolofEngineering,nhokuUniver8ity

AOba,Aramnaki,AobaFku、Sendaj980-77,Japan

E-majl:maha@mk,ccei、tohoku、acjp

Abstract

Thispaperdevelopsa2-Dextensionofthel-DstabilitytheoryapproachtoequationerroradaptivelIRfilters・Thenanalgorithmbasedontheb誠kpropagationfbrmulationof2-DequationerroradaptivelIRfilterswithseparabledenominatorfunctionisproposedanditsconvegenceanalysisisconsidered・Thisalgorithmisbasedontheconceptofb“kpropagatingthedesiredsignajthroughacascadeofthedenominatorvertica1and

horizontalpartssothattWolinearerrorfimctionscanbegenerated・Simulationresults麺epresentedtoshowthattheproposeda1gorithmconvergestotheoptima1solutionwhenthedesiredsignalisfreefromadditive

nmse-However,ifthedesiredsignaliscontaminatedwithadditivenoise,theproposedalgorithmresultsinbiasedestimates・Andthus,abiasremowJmethodanditssimulationresultsarepresented・

keywords 2,equationerroradaptivellRfilter,separabledenominatorbackpropagationllR・filter.

-61-

Page 2: OntheConvergenceof2-DLMSAlgorithm …像2(、,”)麺eline麺withrespecttotheupd孔tedpa戸 rameters麺ldhG1M9ewithgood《9hoi《9eofthestepsize,Eqs.(24)and(29)willconv燈rgetothegloMminimum

1INTRODUCTION

Inre(9entye麺sthereha烏been麺lincreasinginterestintwo-dimensiona雌MiaptiveIIRfilteralgorithmsduetotheirapplicationt⑥imageenhancementandnoise

reduction・TWomain叩proaタhestoadaptivelIRiil‐teringbasedOndi俄renterrorcriteriahfwebeencon‐

sideredsof遼.Thefirstoneisbasedontheoutputerrorfbrmulation,inwhichtheadaptivefilterisup‐dateddirectlyinanllRfbrm・COnsequentlytheme麺

squareoutput-errorisnotquadraticandmaycontajn

severalloca』mini、乱111.Thesecondappro紬isb懇edontheequati(m-errorfbrmulation・Anequ孔tion-erroradaptivellRfilterhassimil麺beh8wiortoanFIRfilter

andthemeansqu麺eequationerrorisquadr亀ticI1l.Tbshimaeta1.I51h2wcextendedthel-D伽kprop‐agationfbrmulationoftheequ孔tionerrorlIRfilters

proposedin14}totwMimensionamRfilte面swithsep‐arabledenomin孔torfmction・Tbmonitorstability§the

a1gorithminI51suggeststh乱tboththedenomin秘tor'sverticalandhorizontalparts麺edecomposedinto孔cas-cadeofse《9ondorder5ections,andhencestabilitymoni‐tOring《9anbeGasilyaXhie”dfbreaXFhl-Dse《9ond-order

section・Howwer,noconvergencean副ysisfbrthe2-DeqllatiOnerrOradaptiveIIRfilterh劇sbeenconsideredsofar・

InthispaPerwefirstdevelopa2-D唾tensi⑧nof

thel-Dstabilitytheoryappro謎htol-Dequationer迄

roradaptivellMltersconsideredi、{21.Thenaユ1a1go‐rithmsimi伽totheoneproposedin{51,butwiththedenomin乱tordecomposedintocascadeofthevertica1

andhorizontalpartsonly麺eproposedanditsconver-

gence麺l遡ysisisinvestigated・Sincetheequationerr(雁basedadaptivealgorithmsgenerallyresultin孔biased

estim孔teswhenthedesiredsigna1iscontaminatedwith

識dditivEnoise,abi殿removalmethodfbrtheproposeda1gorithmaエlditssimulationresultsareconsidered、

22-DBACKPROpAGATIONADAPTIVEIIRFILTERALGORITHM

Thel-DequationerrorlIRfiltersusingthebaXkprop-ag乱tionfbrmulationI4}canbedirectlyextendedtothe2-DcaseasshowninFi9.1.InthisstrUcture,theinputsignalu(m,"),m=0,…,M,仰=0,...,Ⅳ,ispiissed

throllghthefiltertransversalsectioM(qrI,嘘i),whilethedesiredsignaM(m,仰)isba心kpropag孔tedthrollghtheinverseofthea1l-polesectionB(9r',嘘'),where9r1and嘘’麺eusedthroughoutthispapertode‐notetimedelayoper秘torsinthehorizontalandverti戸

caldirectionrespectivelymheeqll秘tionerror侭(m,、)isgeneratedusingtheintermedi乱tesigna1sy,(m,泥)and。,(、,仰)asfbllOws:

e(m,”)=d,(m,沌)-〃,(m,卸)

=怠(qrI,嘘')d(m,,、)一A(9『',嘘')秘(m,沌),(')

wherethefilter'str麺sversalsectionA(9r1,951)andtheinverseoftheallpolesectionB(9r1,嘘I)aregivenby

jV1Ⅳ2

A(‘『!,嘘!)=EEα(#,j)9r‘嘘j (2)j=Oj=0

$§

Figurel:E《lllati《)nErr《)rFormlllatiollfbr2-DIIRFil‐ter.

M1Mコ

B(q『1噸!)=1-EE6(i,j)9「‘塀(3)爵訴o

BysllMitutingEqS.(2)麺d(3)intoEq.(1)andre‐arr皿ging,theα”orpredictionequ勘tionerrore(k)=e(、,")Caユlbewrittenasfbnows:

℃(k)=‘(m,抑)一タT(ルー1MA)=8Tや(A)一jT(ルー1Mル)

=jT(ルー1MA),(4)

whereルーmM+ndenotestheiterationnumber,and

OT={6('’0),…,6(M1,0,)…,6(M1,M2)

α(0,()),…,α(Ⅳ1,()),...,卿(jVl,jV2)1(5)

やT(A)=【例(m-',抑),…,、(m一M,,"),…,d(m-M1,”-雌)趣(m,”)・・・

u(m-Nl,”),…,1』(m-jVI,”一脇)1(6)

jT(ル)=Iih:('’0),…,6k(M,’0),・・・’6k(M,,雌),

。M0,0),…,‘iWV1,0),…,dWV1,M)}(7)

jT(k)=87-タT(ん).(8)

ThetildfDWiⅢ〕ellsedtodelM》tetheerrorintheesti‐

matedentitiesthrollghoutthisp叩⑧r、The2-DLMSEquationError(LMSEE)遡gorithm

fbrth催strll(9tllregiveninFig、1h怨thecoefficientsllPd孔tePr⑧(9edureinthefbrm:

β(ル)=8(ルー1)+ノ"(ル)や(ル),(9)

whereノ↓>Oisthepamnleter'supdatestepsize・Sincetheerrorfimctione(A)isline麺withrespecttotheco‐

efIi(ientsof9(A)themean-sqll麺e-equationerrorisaquadraticfilnctiOnwithasinglegloMminimumand

nolocalminimaI1l.Con蔦equentlyうtheconvergeIM:eoftheprocedureinEq.(9)isonlyrel孔tedtOthestep制zeノ‘,麺dhencefbrsufn《,ientlysm棚lノ‘,Eq.(9)winlmiquelyconvergewithouttheproblemofpammeterinstability・nestablishtheconditionfbrthe《9onver‐

gence,inthefbuowingse(2ti(mthest小ilityappro錘h

tothel-DequationerrorllRfilterconsideredinI2]isextendeddirectlytothe2-Dcase.

-62-

Page 3: OntheConvergenceof2-DLMSAlgorithm …像2(、,”)麺eline麺withrespecttotheupd孔tedpa戸 rameters麺ldhG1M9ewithgood《9hoi《9eofthestepsize,Eqs.(24)and(29)willconv燈rgetothegloMminimum

3STAmmTYnHEORyAPPROACHTO2-DADAPTIVEHRFIⅡmlBR

SUbtr“tingbothsidesofthe孔daPtivealgorithmillEq.(9)fromatimeinv狐ant9,andusingEq.(4)yield

タ(片)={1-坪(k)や(k)Tlj(ルー').('())

ThestabilityapproiM・htoadaptivep麺immeteresti‐

mationconsidersEq.(38)asatime-viiJWingsy葛tem・

Showingth乱t8→0,oreqllivalentlythatl9→0,fbr

anyfinite8(0),《:anbedonebyprovingEq.(38)tobe

gloMly麺d識ymptOticallystable・FortheerrorSystemofEq.(38),c(msiderthefbl‐

lowingLyapllnovfimction:

v(A)=タT(ん)j(A),(1')

whichiseqllaltothe勝11mmation⑥fthesqll麺ederrorsinthep麺amete齢estim孔tGs・If

△V(A)=V(ル)-V(&-1)<0 (12)

fbra』lkandV(0)isfinite,then△V(k)→0.Simil麺tothel-Dc悉e、evalll孔tingEq.(12)yield鰍

△V仏)=-似e2(ル)12-”(k)Tや(A)1.(13)

Sinfe/&isdefinedaspositive,if

O≦仏≦や(蒜町 (14)

fbrall除amsomeグE(0,2),thenEq.(12)iss孔tisfied,and△V(A)→Oimpliesthat川2(k)→O0r

e(A)=jT(ルー'MA)→0. (15)

NotethatEq.(14)implicitlyassumestha岬(A)is

boundedorthattheinput秘isboundedandB(9rlJ嘘')isstable、Moreover,Eq.(15)doesnotimplythat9→0

unlessや(A)issu缶cientlyrichsu<hthat孔no皿ero8isnotorthogonalt叩(jb)加遡M>舟(2),i、e,,orequiv‐alentlyI21Pissuffi(ientlyri('htoex(:iteeverymodeoftheplaエltsuchthaterrorsinidentifyinganyofthese

models麺eol〕servableinthepredicti⑪nGrr()r・

Simil麺tothel-DequatiOnerr⑥r,it(秘nbGe概一

ilyshownthatmillimizingthe2-D側uati()nerrorwillresultin孔unbiaAうedP麺麺netersestimatesonlyifthe

desiredsignali爵、()tcontaminatedwithadditivenoisp.

42-DLMSALGORITHMFORBACK‐

PROPAGAnIONADAPTIVEIIRFIL-

TERS1ⅣITHSEPARABLEDENOMINA-

TORFUNCTION

Thetransfbrfunctionof孔separ孔bleden()minator2-DⅢRfilteris

〃(州11=a等言鍔!y (16)

whereBl(9「')andB2(951)a近ethedenomiIl孔torhor‐izOnt拙麺dverti《9狐p麺tsrespectively,anddefined誌mlows:

M1

B!(9「!)='一E61('),「‘('7)i=l

M2

B2(嘘!)='一E62(j)嘘'.('8)j=1

Ⅲ》rsep麺abledenOminatorllRfilters,theanpolese(?-

tionB(q「1,951)inFig.1(謁迩lbedecomposedint()a(9a3(:Meofverti《?a』趣ldhoriz《mtalp麺tsasshowninFig、2.TheolltPutoftheverti《2遡partc極lbeusedasa1AintGrmedi孔tPsign乱t⑥prOdll《getheintermediat俗errore2(、,仰)whichisline麺withrespe(:ttOthe(9oeffi(:側tsoftheverti《9alP極t・Theintermedi孔teerrorfml《?tionse,(m,")趣lde2(m,仰)麺egivenby

c,(m,,、)=白,(qr1)d2(m,勉)-A(9『',嘘')狸(m,,、)('9)

e2(m,抑)=白2(婚I)。(m,抑)一y2伽,仰),(20)

where

y,(、’'2)=狐(m,加)A(9「',嘘')(2')1

12("2,")=諏雨'!("2,")(22)《12(m,,')=豆2(応')d(m,,z).(23)

Thefiltercoefficientsofthetr麺sversalpartA(9r1,嘘l)池dthedenominat()rhorizontalpartB,(qr1)a正e,,p‐dated細fbnows:

ac?(&)91(A+')=81(い-メ‘'師7両

=8,(ん)+ノ‘,e,(片)や,(jb),(24)

where,

9,=Iル,(1),…,6,(M,),α(0,0),…(25)

α(jV1,()),…,α(jV,,M)17, (26)

j,(A)=隣('),…,鉾(M1),iij,((),0),…,

aと(jv,’0),…,fiAs(Ⅳ,,jv2)lT (27)

P,(片)={m2(m-1,,2),・・・’ぬ(m-M1,”),江(、.”),…,

〃(m-jV,,仰),…,'4(m-jV,,”-M)17,. (28)

A11dthe(9《)efHcientsofthedellomin孔torverti(9a1P孔rtB2(嘘I)麺ellpdatedllsingl-DLMSalgorithmaMbl‐lows:

脚=鑑Iル‘噸淵=iMi(j)+似2忽2(ル)伽,”-j),

j=1,…,雌.(29)

B()thoftheilltermedi孔teerrorfimctionse,(、1,”)and像2(、,”)麺eline麺withrespecttotheupd孔tedpa戸rameters麺ldhG1M9ewithgood《9hoi《9eofthestepsize,

Eqs.(24)and(29)willconv燈rgetothegloMminimumwithouttheproblemofst孔bilitymonitOring・

Theerrorfim(tioninEq.(19)c麺lbewrittenasfbll《)ws:

Cl(m,")=心(m,")-97(ルー1)や,(除).(3())

Ifwedefinedthefbnowingve《9tors:

82={’一&2('),…,一MM2)]T, (31)

タ2(ル)='’一錐('),…,-鑑(M2)17,, (32)

や2(ル)=I‘(m,'、),・・・,d2(m,”-雌)}T,(33)

thenfromFig、2,.2(m,仰)c麺bewrittenas

心(m,")=ぬ(k)=鰯(ルー')や2(A),

={9J-厨(ルー'岬2(k).(34)

-63-

Page 4: OntheConvergenceof2-DLMSAlgorithm …像2(、,”)麺eline麺withrespecttotheupd孔tedpa戸 rameters麺ldhG1M9ewithgood《9hoi《9eofthestepsize,Eqs.(24)and(29)willconv燈rgetothegloMminimum

‘(州)='側…㈹(州-ⅧI;'㈹DiMi+'(j)=錐(j)+似2c2(ル)I。(m,”-j)-

m(ル)e・(m,'n-j)1,j=1,…,雌,(43)

where,e,(ル)i静anerrOrvectordefinedas幼nows

e,(ル)=Ic2(m,”),e2(m-1,抑)…種2(m-M1,")1,(坐)

a、,γ,(A)and通(ル)麺etwova配i小les,theirvalues麺echOselltov8LrybetwGenO孔tthebeginingoftheadaptiveprocessandincreaSegraduallytol懇e‘(k)皿de2(k)tendtobemore誠curateestimatesoftheadditivenoiseiM(ん)anM2(k)respGctively、Andthusγ,(A)皿dな(k)錘edefinedasfbllows

両(…(“綴淵),,≦鰯,≦'’㈹州=唾(い,淵{),,≦"≦'’㈹wherelllldenotestheEu《:lideannorm,伽

e2(ん)=IC。(m,”),c・(m’'@-1)…c・(m’'@一雌)1.(47)

Itc麺bee錨ilyBhownthat

8作j(ん)=恥2(ル),(35)

andthusbysllbstitutinginEq.(34),wecanwriteEq.(30)asfbllows

e,(m,")=j,(ルー1)γや,(A)-激ルー1)w(A).(36)

Now,subtractingbothsidesofEq.(24)fromthetimeinvaエiimt81andusingEq.(36)wehave

O,(ル)=11-ノ‘,や,(jWj(k)Tlj,(ルー')一M?(ルー1)鞄(ルM(た).(37)

Bytakingtheexpe《:tedvalueof(37)wehave

EI8i(ル)l=E{('一脚,やI(ん)や,(た)T)‘,(た一')1

-メ‘,E{鱒(ルー'沖2(た)?,側,=EIA,81(た-1)1-脚E{A2や,(A)1,(38)

AconvergenceanalysisbasedonLyapunovstabilitytheorycanbeappliedtotheiirsttermofEq.(38)anditcanbeshownthatif

。≦‘‘,≦*、(")where入,…塚denotesthemaximumeigenv5Jueof

Rや,や,=や,(ル)や,(A)T, (40)

thentheeigenvaluesofA1areallinsidetheunitcircle麺dhencethefirsttermisanasymptoticallystableandandc《)nvergetozero・ThestabilityofA2inthesecondtennofEq.(38)isrelatedtotheconvergenceofEq.(29)whichc型beconsideredasal-DLMSa1gorithmfbrtimevaエyingFIMlterwithaninputsignaM(k)andanonstationa歴ydesiredoutputy2(k).Theconvergenceanalysisandtheoptimalchoicefbrthestepsizeノj2c皿becamiedoutasdiscussedin{71.Bychoosingthestep副Ze〃,smanenOugh,theoutputy1canbeconsideredtobestationaryoverasmaJlwindow・Andthusifthestepsizeノ82satisfies

,≦似2≦*テ(")where入2m。錘denotesthemaxlmum画genvalueof

nP2や2=や2(ハル2(k)T, (42)

thenEq.(29)is翁tableandO2(ル)→OandhencethesecondterminEq.(38)isstableandwinconvergetoZerO.

The、趣ndrawb&Mkoftheequ孔tionerror-basedadap-tiveIIRfilteristhatit《Bonvergesto孔biasedestimateswhenthedesiredsignaliscontaminatedwithadditivenOise・Tbremovesuchbias,inthel-Dequationerror

adaptivellRfilterLinetal.{6]hasproposedabiasrem‐edyalgorithmwhichusetheOutpllterror調anestima戸tionfbrtheunkn⑨wn湖ditivenoise.R》rthea1gorithmproposedinSection4wecannotice(seeFig.2)thattheoutputerrore。(A)canbeusedasanestimationoftheadditivenoiseinthedesiredsignaM(ル),whiletheintermedi職teerrore2(A)canbeusedasanestimationofthe副dditivenoiseintheilltermediatesignaM2(A).Andthustheupdateproceduresin(24)麺。(29)c麺lbemodifiedaMbnows

gU 9,‘ 、)

、 、

Figure2:Eqllati《)nErrorR)rmulationfbrSep麺ableDenomin孔tor2-DIIRFilter.

5BIASREMOVALALGOmTHM

H(9「’

6SIMULAnlONRESUI/rS

Examplel:Inthisexammplethealgorithmis叩pliedtotheSystemidelltificationconfigurationasshowninFi9.3,wheretheinputisa2-DzeromeanwhiteGaus‐siansign釧ofsize250by250andunitvarlamlce・AndtheMditivenoiseissettozero・Thefbllowingsep麺缶bleden⑪minatorfimctionisused識thetr麺葛娩rfilnc‐

tiOnfbrtheunknownsystem.

1+0.89『'一().5嘘'-0.49『'痕’

,嘘')=(1-1.29「'+0.369『2)(1+0.9盛'+0.2嘘2),

E(j)

-64-

1,Fig.4weshowthec⑥nvergenceofoutputerror-basedfi、《9tiongwhi征hisdefinedasfbllows

=死圭万蔓c・(j,j)2+c。(j,j)2,0≦堪皿-1.

Page 5: OntheConvergenceof2-DLMSAlgorithm …像2(、,”)麺eline麺withrespecttotheupd孔tedpa戸 rameters麺ldhG1M9ewithgood《9hoi《9eofthestepsize,Eqs.(24)and(29)willconv燈rgetothegloMminimum

Insuchnoisefreecase,theproposedalgorithma1‐

w2Wsshowsfast麺dcompleteconvergencetotheopti‐m狐solution・

ExanlPle2:InthisexampleaZeromeaエ1,Unitvari‐an(?eGaussiannoisewhichisindependentoftheinpllt

sign狐isusedfbrtheadditivenoisew・Theinputsigna1麺dtheunknownSystem麺easdeiinedinExamplel・

The(9onvergenceoftheoutputerrorusingthebiasre‐movalalgorithmpmposedinSection5isshowninFi9.5.Theresultedpar6hmetersestimat鴎withandwithoutbiasremovalareshOwninI泡bleloFromtheseresults

itisde麺thatthebiasresultedfromtheadditivenoise

inthedesiredsignalwasconsiderablyredUced

nblel:ParametersEstimateSfbrEx麺nples2.

EZmSVerSalSeC

TrllevaueS

oval

|綴r《mmovw1

D(麺omin誠or

nmevnhle

with

bias

ovlhl

rfmmowhl

a(1,0)0.8

1.3065

0.8019

b,(1) b,(2)-1.2 0.36

-0.7187 -0.1135

-1.2044 0.3570

孔(0,1) a(1,1)-0.5 -0.4

-0.4841 -0.6198

--0.5233 -0.3747

b2(1) b2(2)0.9 0.2

0.9055 0.2206

0.8958 0.1998

Ex&mlple3:Inthisexampleweapplytheproposedalg⑧rithmtoa2Dad紐PtivelineenhancementasshowninFi9.6,thedesiZedsignaMistheoriginalimagelena(蔦eeFig、7)degr掴edwithzeromeanwhiteGauss伽noiseT).TheinputimageisadelaWedversionofthedesiredimageobtainedasfbllOw葛

Ⅶ(、,仰)=。(m-1,”-1).(48)

Boththeva皿?1麺cesoftheadditivenoiseUa1ldthe

theoriginalimagG;raresettoO、2.Theinputandolltplltim略esofthe2DadaptivelineEnhancementwiththeircorrespondingMe皿Squ麺eError(MSE)valuesareshowninFig、8and9rEsPectively・WherPtheMSEisdeiinedasfbnows

班SE=E{Mm,仰)-蕪(m,”)12}(49)

7CONCLUSION

Inthispaperwehfwedevelopedthe2-Dextensionofthel-DstabilityaPproaX9htdequationerroradaptivefilters,Thenthe2-DLMSalgorithmfbrseparable

denominatorllRiiltersanditsconvergencestabilityh8webeenconside顕d・Thisalgorithmisbasedontheconceptofba妃kpropagatingthedesiredsignalthroughacascadeofthedenominatorverticalandhoriz《》ntaJ

partssOthattwOline麺errorfmctionscanbegener‐帥Gd・Simul孔tionrPsllltswerecarriedollttoevalllate

theperfbrm麺ceoftheproposedalgorithm・Fornoisefreecasetheproposeda1gorithmhasconvergedtothe

Optimalsol'1tionwitholltbiasintheparametersesti-

m孔tes・However,smcetheequationerror-basedadap‐●

tivealgorithmsgenerallyresultinabiasedestimates

whenthedesiredsignalisc()ntaminatedwithadditivelloise,abiasremovalmethodhrtheproposedalgo-rithmhasbeen《9onsidered、Simnllationresultswerealso

presentedtoshowthee仇ctivenessofthismeth⑥..

、刑FERENCES

111W.K・Jenkins,A、W,Hul1,J.C、Str麺t,B、A、S(:hnaufer,麺ldX・Li,AdvancedConcepts

inAdaptiveSignalProcessing,KluwerAcademicP11blishers,1996.

I2lC.R、Johnson,JR,"AdaptivelIRFiltering:Cur‐rentResultsandOpelllsslles,,,IEEE、?ans.I、‐

f)rm・Theory,vol・IT-30,pp、237-250,Mar.1984.

131J.J、Shynk,"Ad乱ptivelIRFiltering,"IEEEASSPM略.,pp、421,Apr、1989.

{4]F,X、Y・Gaoaエ1.W.M、S11elgrove,“AnAdap‐tiveBax2kpropagationCascadellRFilter,'’1EEEnans・CircuitsSyst・’1,vol・CAS-39,no、9,pp、

606-610,Sept、1992.

151K.Ibshim秘,M,Ohki,andX・Zhou,H,Hashiguchi,“2-DB誠kpropagationC躯(9adeAdaptiveRecllr‐siveFilterwiththeSep孔rableDenominatorhnc‐

ti⑪、,,,ThirdlnternationalSymposiumonCon‐

sumerElectronics,vol、2,pp、441-446,Nov、1994.

161J.N、Lin,R、Unbehanen,“Bias戸RemedyLeastMeanSqu錘eEquationErrorAlgorithmfbrllR

PammeterRecursiveEstimation,”IEEETra1ls・

Sign副Processing,vol、40,no、1,pp、62-69,J麺1.1992.

I71S・Haykin,AdaptiveFilterTheory,NJ:Prentice‐Hall,Thirdedition,1996.

Figure3:2DSystemIdentificationConfiguration

-65-

Page 6: OntheConvergenceof2-DLMSAlgorithm …像2(、,”)麺eline麺withrespecttotheupd孔tedpa戸 rameters麺ldhG1M9ewithgood《9hoi《9eofthestepsize,Eqs.(24)and(29)willconv燈rgetothegloMminimum

。』

..…・・・…・・withbiasremoval

withoutbiasremoVal

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1、01

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IlwM…!目

蕊%50100150200250

IterationNUmberi

Figllre7:Originallmage

Figure4:CoIwergenceoftheoutputerrorfbrnoisefreecase(Examplel)

Input

imagezL伽,、ノ

-66-

--7---------…--‘

Iterl2DAdaptivefi

F一ー一ーーー--画一一画■再一一一一一一E

% 5010 0 1 5 0 2 0 0 2 5 0

1terationNUmberi Figure8:InplltlmagP,MSE=0.0467,

Figure5:Converge1lceoftheolltputerrorofthebiasremovalalgorithm

F一ー一ーーー--画一一画■再一一一一一一E

Figure6:2DAdaptiveLineEnhancement

m

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gorithmLlAdaptivealI

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gorithmLlAdaptivealI