简介：SeveralARMAmodelingapproachesareaddressed.Inthesemethodsonlypartofacorrelationsequenceisemployedforestimatingparameters.Itissatisfying,ifthegivencorrelationsequenceisofrealARMA,sinceanARMAprocesscanbecompletelydeterminedbypartofitscorrelationse-quence.Butforthecaseofameasuredcorrelationsequencethewholesequencemaybeusedtore-ducetheeffectoferroronmodelparameterestimation.Inaddition,thesemethodsnowdonotguar-anteeanonnegativespectralestimate.Inviewoftheabove-mentionedfact,aconstrainedleastsquaresfittingtechniqueisproposedwhichutilizesthewholemeasuredcorrelationsequenceandguar-anteesanonnegativespectralestimate.

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简介：Stochasticadaptivecontrolisconsideredforthediscrete-timemulti-inputandmulti-outputsystemofmulti-delaywithnoiseexpressedbyanARMAprocess.TheCARIMAmodelisaspecialcaseofthesysteminquestion.Theoptimaladaptivecontrollawisgivenanditisshownthataquadraticcostfunctionisminimizedandtheclosed-loopsystemisstable.Further,whenthesystemisofminimumphase,theconvergenceratesofparameterestimatesandofthecost-functionarealsoderived.

简介：Atimeseriesx（t）,t≥1,issaidtobeanunstableARMAprocessifx（t）satisfiesanunstableARMAmodelsuchasx（t）=a1x（t-1）+a2x（t-2）+…+a8x（t-s）+w（t）wherew（t）isastationaryARMAprocess;andthecharacteristicpolynomialA（z）=1-a1z-a2z2-…-a3z3hasallrootsontheunitcircle.Asymptoticbehaviorofsumform1ton（x2（t））willbestudiedbyshowingsomeratesofdivergenceofsumform1ton（x2（t））.ThiskindofpropertiesWillbeusedforgettingtheratesofconvergenceofleastsquaresestimatesofparametersa1,a2,…,a?

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简介：Basedonthemulti-sensoroptimalinformationfusioncriterionweightedbymatricesinthelinearminimumvariancesense,usingwhitenoiseestimators,anoptimalfusiondistributedKalmansmootherisgivenfordiscretemulti-channelARMA(autoregressivemovingaverage)signals.Thesmoothingerrorcross-covariancematricesbetweenanytwosensorsaregivenformeasurementnoises.Furthermore,thefusionsmoothergiveshigherprecisionthananylocalsmootherdoes.

简介：StatisticalpropertiesofwindsneartheTaichungHarbourareinvestigated.The26years′incompletedataofwindspeeds,measuredonanhourlybasis,areusedasreference.ThepossibilityofimputationusingsimulatedresultsoftheAuto-Regressive(AR),Moving-Average(MA),and/orAuto-RegressiveandMoving-Average(ARMA)modelsisstudied.Predictionsofthe25-yearextremewindspeedsbasedupontheaugmenteddataarecomparedwiththeoriginalseries.Basedupontheresults,predictionsofthe50-and100-yearextremewindspeedsarethenmade.

简介：针对反坦克导弹系统动态过程仿真的输出具有短时序、低信噪比的特点,研究了应用ARMA谱估计验证导弹系统仿真模型有效性的方法,并结合某型号滚转稳定的反坦克导弹系统复杂模型的仿真数据和简化模型的仿真数据给出ARMA谱估计的应用结果.

简介：提出了双轮辙路面不平度激励的时域AR及ARMA模型，并对所建立的模型进行了计算机数值仿真研究。