基于LMS的自适应滤波器典型应用的MATLAB实现

LMSMATLAB王益根(,225009):介绍了自适应滤波器的原理和最小均方(LMS)算法,并且利用MATLAB实现了自适应系统辨识和自适应干扰抵消:自适应滤波;最小均方算法;MATLAB:TP273+.2:A:1008-3693(2007)02-0035-03TheRealizationofAdaptiveFilterbasedonLMSbyApplyingMATLABWANGYigen(YangzhouPolytechnicCollege,Yangzhou225009,China)Abstract:ThepaperintroducesthetheoryofAdaptiveFilterandLMS(leastmeansquare)algorithm.Meanwhile,itmanagestouseMATLABtorealizetheadaptivesystemidentifierandinterferencecancellation.Keywords:adaptivefilter;LMS;MATLAB,,,,LMS,MATLAB1(Adaptivefilter),,,[1]IIR,,FIRFIR11FIR,(LMS,leastmeansquare):2007-03-30:王益根(1974-),男,扬州职业大学电子工程系助教11220076JournalofYangzhouPolytechnicCollegeVol.11No.2Jun.2007,,[2,3]1.1LMS算法的基本过程LMS,1,x(n),y(n),d(n),e(n)d(n)y(n)e(n),e(n):x(n)M,1:y(n)=N-1k=0h(k)x(n-k),n=0,,Me(n)d(n)y(n),,e(n)=d(n)-y(n),n=0,,M=Mn=0e2(n)=Mn=0[d(n)-N-1k=0h(k)x(n-k)]2,{h(k)},,LMS1.2LMS算法的具体步骤LMS,{h(k)},{x(n)}FIR,{y(n)},e(n)=d(n)-y(n),hn(k)=hn-1(k)+e(n)x(n-k),0!k!N-1,,x(n-k)nk,e(n)x(n-k)k()2MATLABMATLABADAPTLMS,ADAPTLMS:[y,e,s]=ADAPTLMS(x,d,s)y,x,d,e,s,INITLMSINITLMS:s=INITLMS(h0,Mu)h0,0;Mu331系统辨识,,NFIR(,2),FIR,x(n){y(n)},{d(n)},e(n)=d(n)-y(n),,,LMSFIR,:2x=01*randn(1,500);%x(n)b=fir1(31,05);%FIRd=filter(b,1,x);%d(n)w0=zeros(1,32);%mu=08;%LMSS=initlms(w0,mu);%s[y,e,S]=adaptlms(x,d,S);%stem([b.∀,S.coeffs.∀]);%361133,32自适应干扰抵消,,4,d(n)s(n)n1(n),d(n)=s(n)+n1(n),n2(n)n1(n),,y(n)n1(n)n^1(n),e(n),n1(n)[4]4:N=500;noise=[sin(2*pi*0015*[0:N-1])05*cos(2*pi*0008*[0:N-1])];%d=noise;nvar=05;s=nvar*randn(1,2*N);%n=sig+noise;M=32;%mu=02;%LMSS=initnlms(zeros(1,M),mu);%s[y,e,S]=adaptnlms(n,d,S);%stem([y∀,d∀]);%5LMS5,,s(n),:(1)n1(n)n2(n),n2(n)s(n),;(2)s(n),,4,,,:[1].TMS320VC5402[J].,2006,37(6):816-819.[2]K,G.MATLAB[M].:,2002.[3],,.[M].:,2003.[4].[M].:,2002.372:LMSMATLAB