简介：

简介：在这篇论文，我们学习僵硬地加权的假逆(W~(1/2)A)的不安~(匕首)W~(1/2)和相关僵硬地加权的最少的广场问题，在矩阵A和W与W被给的地方积极斜、严重地生硬。我们证明到僵硬地加权的假逆和相关僵硬地加权的最少的广场问题的不安是稳定的，如果并且仅当使不安的矩阵A=A+δA满足保存条件的几个排等级。

简介：Manyreal-worldsystemscanbemodeledbyweightedsmall-worldnetworkswithhighclusteringcoefficients.Recentstudiesforrigorouslyanalyzingtheweightedspectraldistribution(WSD)havefocusedonunweightednetworkswithlowclusteringcoefficients.Inthispaper,werigorouslyanalyzetheWSDinadeterministicweightedscale-freesmall-worldnetworkmodelandfindthattheWSDgrowssublinearlywithincreasingnetworkorder(i.e.,thenumberofnodes)andprovidesasensitivediscriminationforeachinputofthismodel.ThisstudydemonstratesthatthescalingfeatureoftheWSDexistsintheweightednetworkmodelwhichhashighandorder-independentclusteringcoefficientsandreasonablepower-lawexponents.

简介：

简介：ItisshowninthispaperthatahyponormalweightedshiftofnormoneisunitarilyequivalenttoaToeplitzoperatorifandonlyifitsweights{an}0∞satisfy1-丨an丨2=（1-丨a0丨2）n+1n≥0.Inparticular,thisanswerstheAbrahamse’sProblem2.Asaconse-quence,the（surprising）answer,obtainedfirstbyC.C.Coweninanexplicitform,toHalmos’Question5isrecaptured.

简介：Givenanadmissibleweightwand0

简介：InthissurveythenotionofabalancedbestmultipointlocalapproximationisfullyexposedsincetheyweretreatedintheLpspacesandrecentresultsinOrliczspaces.Thenotionofbalancedpoint,introducedbyChuietal.in1984areextensivelyused.

简介：Let(Ω,A,P)beaprobabilityspace,X(t,ω)arandomfunctioncontinuousinprobabilityfort∈[0,∞)or(-∞,+∞)(ω∈Ω),andF(t)apositivefunctioncontinuousfort∈[0,+∞)or(-∞,+∞).IfX(t,ω)andF(t)verifycertainconditions,thenthereexistaasequence{Qn(t,ω)}ofrandompolynomialssuchthatwehavealmostsurely:fort[0,+∞)or(-∞,+∞),lim↑n→+∞|X(t,ω)-Qn(t,ω)|/F(t)=0.

简介：Theaimofthispaperistodevelopanorderedweighteddistance(OWD)measure,whichisthegeneralizationofsomewidelyuseddistancemeasures,includingthenormalizedHammingdistance,thenormalizedEuclideandistance,thenormalizedgeometricdistance,themaxdistance,themediandistanceandthemindistance,etc.Moreover,theorderedweightedaveragingoperator,thegeneralizedorderedweightedaggregationoperator,theorderedweightedgeometricoperator,theaveragingoperator,thegeometricmeanoperator,theorderedweightedsquarerootoperator,thesquarerootoperator,themaxoperator,themedianoperatorandtheminoperatorarealsothespecialcasesoftheOWDmeasure.SomemethodsdependingontheinputargumentsaregiventodeterminetheweightsassociatedwiththeOWDmeasure.TheprominentcharacteristicoftheOWDmeasureisthatitcanrelieve(orintensify)theinfluenceofundulylargeorundulysmalldeviationsontheaggregationresultsbyassigningthemlow(orhigh)weights.ThisdesirablecharacteristicmakestheOWDmeasureverysuitabletobeusedinmanyactualfields,includinggroupdecisionmaking,medicaldiagnosis,datamining,andpatternrecognition,etc.Finally,basedontheOWDmeasure,wedevelopagroupdecisionmakingapproach,andillustrateitwithanumericalexample.

简介：称为介绍的加权的随机整修的meansare和不仅他们的一致性和asymptotic规度的柔韧的地点评估者的一个班被证明，但是theirinfluence工作asymptotic变化和故障点也被导出。他们拥有是的thesame故障点中部，并且他们中的一些拥有更高的asymptotic亲戚效率atthe重尾巴的分布比一些另外的著名地点评估者；而trimmedmeans，Winsorized工具和Huber“sM评估者拥有更高的asymptotic亲戚效率atthe跟踪光的分布，在哪个Huber”sM评估者是最柔韧的。

简介：WestudytheboundedandthecompactweightedcompositionoperatorsfromtheBlochspaceintotheweightedBanachspacesofholomorphicfunctionsonboundedhomogeneousdomains,withparticularattentiontotheunitpolydisk.Forboundedhomogeneousdomains,wecharacterizetheboundedweightedcompositionoperatorsanddeterminetheoperatornorm.Inaddition,weprovidesufficientconditionsforcompactness.Fortheunitpolydisk,wecompletelycharacterizethecompactweightedcompositionoperators,aswellasprovide'computable'estimatesontheoperatornorm.

简介：Inthispaper,weproposetwoweightedlearningmethodsfortheconstructionofsinglehiddenlayerfeedforwardneuralnetworks.Bothmethodsincorporateweightedleastsquares.Ourideaistoallowthetraininginstancesnearertothequerytoofferbiggercontributionstotheestimatedoutput.Byminimizingtheweightedmeansquareerrorfunction,optimalnetworkscanbeobtained.Theresultsofanumberofexperimentsdemonstratetheeffectivenessofourproposedmethods.

简介：ThereseearchontherelationbetweenweightedshiftoperatorsonHilbertspacesandotherimportantclassofoperatorsattractedtheattentionofsomemathematicians.Forexample,therelationbetweenweightedshiftoperatorsandsubnormaloperatorshasbeenthoroughlystudiedbyJ.Stampfli,R.GellarandD.A.Herrero,etc.(seereference[1])Butthedecomposabilityofweightedshiftoperatorshasnotyetattractedenoughattentionuptonow.Wemadeinitialresearch

简介：Theweightedreliabilityofnetworkisdefinedasthesumofthemultiplicationoftheprobabilityofeachnetworkstatebyitsnormalizedweightingfactor.Underacertainstate,whenthecapacityformsourcestosinktislargerthanthegivenrequiredcapacityCr,thenthenormalizedweightingfactoris1,otherwise,itistheratioofthecapacitytotherequiredcapacityCr.Thispaperproposesanewalgorithmfortheweightedreliabilityofnet-works,putsforwardtheconceptofsaturatedstateofcapacity,andsuggestsarecursiveformulaforexpandingtheminimalpathstobethesumofqualifyingsubsets.Inthenewalgorithm,theexpansionsoftheminimalpathsdon'tcreatetheirrelevantqualifyingsubsets,thusdecreasingtheunnecessaryexpandingcalculation.Comparedwiththecurrentalgorithms,thisalgorithmhastheadvantageofasmallamountofcomputationsforcomputerimplementa-tion.

简介：由一个基本证明，我们使用Conway和Dudziak的结果看那A是否是一个hyponormal操作符与光谱半径r(A)以便它的光谱是关上的磁盘{z:|z|r(A)}当时，A是反射的。用这结果，我们在移动操作员的reflexivity上给Bercovici，Foias，和Pearcy的结果的一个简单证明。另外，可颠倒的双边的加权的移动的每力量是反射的，这被显示出。

简介：这份报纸被奉献在同类的组X上学习加权的强壮的空间的原子分解。一些结果是在欧几里德几何学的泛音分析学习的对象的扩展。

简介：在网络的社区察觉在最后十年广泛地被学习了。许多标准，表示分区的质量获得，以及一些准确算法和很多启发规则被建议了。吝啬标准在最小化增加或从给定的网络搬迁了以便把它转变成一套disjoint派系的边的数字在于。最近，张，丘和张建议了一个重量系数在被介绍平衡插入并且删除的边的数字的一个加权的吝啬模型。这些作者建议规则选择系数的好值，使用模仿了退火发现最佳或在最佳附近的解决方案并且解决一系列真实、人工的例子。在现在的纸，一个算法为确切为参数的所有价值解决加权的吝啬问题被建议。这个算法反复地基于用一个排产生算法为参数的一套给定的价值解决这个问题。这个过程与一个搜索过程被相结合发现值曲线的所有最低断点即，插入并且删除的边的加权的和。从文学的一系列人工、真实的世界网络上的计算结果被报导。看来，为一样的几个分区联网可能增进知识并且解决方案的集合通常包含至少一个直觉地呼吁的分区。

简介：<正>SupposeXisasuperdiffusioninRdwithgeneralbranchingmechanism￠.andYDdenotesthetotalweightedoccupationtimeofXinaboundedsmoothdomainD.WediscusstheconditionsonψtoguaranteethatYDhasabsoluteycontinuousstates.Andforparticularψ（z）=z(l+,0DisabsolutelycontinuouswithrespecttotheLebesguemeasureinD.whereasinthecased>2+2/B.itissingular.AsweknowtheabsolutecontinuityandsingularityofY(Dhavenotbeendiscussedbefore.

简介：MostexistingapplicationsofcentroidalVoronoitessellations(CVTs)lackconsiderationofthelengthoftheclusterboundaries.Inthispaperweproposeanewmodelandalgorithmstoproducesegmentationswhichwouldminimizethetotalenergy—asumoftheclassicCVTenergyandtheweightedlengthofclusterboundaries.TodistinguishitwiththeclassicCVTs,wecallitanEdge-WeightedCVT(EWCVT).TheconceptofEWCVTisexpectedtobuildamathematicalbaseforallCVTrelateddataclassificationswithrequirementofsmoothnessoftheclusterboundaries.TheEWCVTmethodiseasyinimplementation,fastincomputation,andnaturalforanynumberofclusters.

简介：在这篇论文，我们在联合起来的磁盘D上学习Hakopian插值的加权的吝啬的不可分的集中。我们出现在Hakopian插值多项式Hn之间的内部产品(f；x，y)；光滑的功能g(x，y)在D上收敛到f的(x，y)；g(x，y)在D上什么时候n→8f(x，y)属于C(D)；g的所有第一部分衍生物(x，y)属于空间嘴唇M[α](0<α≤1)。我们进一步证明那提供了g的所有秒部分的衍生物(x，y)也属于空间嘴唇M[α]；f(x，y)属于C[1](D)，在Hakopian插值的部分衍生物之间的内部产品多项式；g(x，y)在D上收敛到那在之间；g(x，y)在D上什么时候n→∞。