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lms算法毕业论文.doc

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lms算法毕业论文.doc

lms算法毕业论文LMS算法研究专业通信工程2摘要因LMS算法具有低计算复杂度、在平稳环境中的收敛性好、其均值无偏地收敛到wiener解和利用有限精度实现算法时的稳定性等特性,使LMS算法成为自适应算法中应用最广泛的算法。对LMS算法及其改进算法进行了研究,探讨了步长因子n对各种算法收敛性、稳定性的影响。并用MATLAB对其学习曲线、收敛速度等进行了仿真分析。结果表明,变步长n的取值尤为重要,如果μ(n)取较大值则具有较快的收敛速度,如果μ(n)取值很小,则MLMS算法近似等效于LMS算法。它们的自适应过程较快,性能有了很大改进。3AbstractBecauseoflowcomputationalcomplexity,stableenvironmentintheconvergenceofgood,unbiasedanditsmeanconvergestothewienersolutionandimplementationalgorithmsusingfiniteprecisionstabilityandothercharacteristics,LMSalgorithmasadaptivealgorithmintheapplicationofthemostawiderangeofalgorithms.WehaveadetailedstudyonLMSalgotithmanditscomplementaryalgotithm,disscusedthestepsizesinfluentforthealgorithmsconvergencespeedandstability.AndusingMATLABsimulatedthelearningcurve,convergencespeedofLMSalgotithm.Theresultobservedthatthevalueofvariablestepsizeμ(n)isveryimportant,ifitisabiggermayhaveafastconvergencespeed,butifnot,theNLMSalgotithmcaninsteadtheLMSalgotithminthecharacteristics.Inaddition,theyhaveafastadaptivecourseandgreatlyprogressinperformance.KeywordsLMSalgorithm,Adaptive,NLMSalgorithm,Variablestep,MATLABsimulation.4目录第一章绪论...............................................................................61.1自适应滤波理论的发展................................................................61.2自适应LMS算法的发展................................................................71.2.1LMS算法历史....................................................................71.2.2LMS算法的现状..................................................................71.2.3LMS算法的发展前景..............................................................7第二章自适应LMS算法的研究...............................................................92.1概述................................................................................92.2LMS算法............................................................................92.2.1自适应收敛性...................................................................112.2.2平均MSE学习曲线............................................................122.2.3失调...........................................................................142.2.4缩短收敛过程的方法.............................................................15第三章LMS自适应滤波器的改进形式.........................................................173.1归一化LMS算法.....................................................................173.1.1TDOLMS算法...................................................................193.1.2MLMS算法......................................................................203.2泄露LMS算法.......................................................................213.3极性LMS算法.......................................................................223.4LMS算法梯度估计的平滑..............................................................223.5解相关LMS算法.....................................................................233.6性能比较...........................................................................24第五章LMS算法的应用....................................................................255.1LMS类均衡器........................................................................255.1.1解相关LMS(DecorrelationLMS,DLMS)均衡算法...................................255.1.2变化域解相关LMS均衡算法.......................................................255.2自适应信号分离器...................................................................265.3自适应陷波器.......................................................................275.4系统辨识或系统建模.................................................................27第六章仿真及其结果分析..................................................................296.1仿真思路...........................................................................296.2结果及分析.........................................................................296.2.1LMS及其改进算法...............................................................296.2.2LMS自适应均衡器...............................................................326.2.3自适应信号分离器...............................................................346.2.4自适应陷波器...................................................................346.2.5系统辨识或系统建模.............................................................34结论.................................................................................36

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