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简介：Twocomplexproperties,varyingtime-delayandblock-orientednonlinearity,areverycommoninchemicalengineeringprocessesandnoteasytobecontrolledbyroutinecontrolmethods.Aimedatthesetwocomplexproperties,anoveladaptivecontrolalgorithmthebasisofnonlinearOFS(orthonormalfunctionalseries)modelisproposed.First,thehybridmodelwhichcombinesOFSandVolterraseriesisintroduced.Then,astablestatefeedbackstrategyisusedtoconstructanonlinearadaptivecontrolalgorithmthatcanguaranteetheclosed-loopstabilityandcantrackthesetpointcurvewithoutsteady-stateerrors.Finally,controlsimulationsandexperimentsonanonlinearprocesswithvaryingtime-delayarepresented.Anumberofexperimentalresultsvalidatetheefficiencyandsuperiorityofthisalgorithm.

简介：Inthispaper,westudyadaptivefiniteelementdiscretisationschemesforaclassofparameterestimationproblem.Weproposetouseadaptivemulti-meshesindevelopingefficientalgorithmsfortheestimationproblem.Wederiveequivalentaposteriorierrorestimatorsforboththestateandthecontrolapproximation,whichparticularlysuitanadaptivemulti-meshfiniteelementscheme.Theerrorestimatorsarethenimplementedandtestedwithpromisingnumericalresults.

简介：WirelessMeshNetworks(WMNs)areenvisionedtosupportthewiredbackbonewithawirelessBackboneNetworks(BNet)forprovidinginternetconnectivitytolarge-scaleareas.Withawiderangeofinternet-orientedapplicationswithdifferentQualityofService(QoS)requirement,thelarge-scaleWMNsshouldhavegoodscalabilityandlargebandwidth.Inthispaper,aLoadAwareAdaptiveBackboneSynthesis(LAABS)algorithmisproposedtoautomaticallybalancethetrafficflowintheWMNs.TheBNetwilldynamicallysplitintosmallersizeormergeintobiggeroneaccordingtostatisticloadinformationofBackboneNodes(BNs).SimulationresultsshowLAABSgeneratesmoderateBNetsizeandconvergesquickly,thusprovidingscalableandstableBNettofacilitatetrafficflow.

简介：为有动态无常的非线性的系统的一个类，柔韧的适应稳定问题在这篇论文被考虑。由介绍一个观察员，第一，一个扩充系统被获得。基于系统，我们构造exp-ISpSLyapunov为unmodeled动力学工作，证明unmodeled动力学是exp-ISpS，然后获得一个动态使动态骚乱正常化信号抵抗。由backstepping技术，一个适应控制器被给，在适应控制系统的所有信号最终一致地全球性被围住，这被证明，并且输出能被调整到有任何规定精确性的起源。一个模拟例子进一步表明控制计划的效率。关键词Unmodeled动力学-Exp-ISpS-动态使中国(号码60304003)和节目的国家自然科学基础正常化信号-Backstepping-适应控制这个工作被在大学里为新世纪优秀才能支持(没有。NCET-05-0607)。苏海霞在2003在Qufu师范大学从数学的部门收到了她的学士学位。当前，她在一样的大学的自动化的研究所正在追求她的硕士学位。她的研究兴趣是非线性的适应控制。谢学军从系统科学的研究所收到了他的博士学位，在1999的中国科学院。他当前是在在Qufu师范大学的自动化的研究所的一个教授。他的研究兴趣为复杂系统包括适应控制。刘海宽在1991点从哈尔滨工学院收到了他的学士学位。他是在Xuzhou师范大学的一个教授。他的研究兴趣包括柔韧的控制，电源来源技术，和计算机有申请的综合系统。

简介：在这份报纸，我们基于间接轻路径复用学习一套全球照明算法的评价变化。这些算法通常在第一张通行证包含二张通行证，间接轻样品的一个小数字被产生并且评估，并且他们然后被很多重建样品在第二张通行证再使用。我们的分析证明重建样品的协变性在高重建率下面统治评价变化并且增加重建率不能有效地减少协变性。我们也发现协变性代表到到什么度，间接轻样品在重建期间被再使用。这分析激发我们设计启发式的接近协变性以及一个适应采样计划基于这对还原剂启发式显示的变化。我们为间接点亮在间接的轻地重建算法和排列轴的过滤算法验证我们的分析和适应采样计划。实验根据我们显示人工制品能极大地以类似的计算成本被减少的分析和表演。

简介：

简介：ThenormalhypervelocityimpactofanAl-thinplatebyanAl-spherewasnumericallysimulatedbyusingtheadaptivesmoothedparticlehydrodynamics(ASPH)method.Inthismethod,theisotropicsmoothingalgorithmofstandardSPHisreplacedwithanisotropicsmoothinginvolvingellipsoidalkernelswhoseaxesevolveautomaticallytofollowthemeanparticlespacingasitvariesintime,space,anddirectionaroundeachparticle.UsingtheASPH,theanisotropicvolumechangesunderstrongshockconditionarecapturedmoreaccuratelyandclearly.ThesophisticatedfeaturesofmeshlessandLagrangiannatureinherentintheSPHmethodarekeptfortreatinglargedeformations,largeinhomogeneitiesandtracingfreesurfacesintheextremelytransientimpactprocess.Atwo-dimensionalASPHprogramiscodedwithC++.Thedevelopedhydrocodeisexaminedforexampleproblemsofhypervelocityimpactsofsolidmaterials.Theresultsobtainedfromthenumericalsimulationarecomparedwithavailableexperimentalones.Goodagreementisobserved.

简介：在这篇论文，一个柔韧的适应控制计划与分离、分布式的延期为不明确的线性系统的稳定被建议并且围住不安。不确定性被假定是有围住标准的限制的未知连续功能。不安是围住扇区的。与班机矩阵不平等方法，神经网络和适应控制结合，控制计划为任何可被考虑的不确定性保证靠近环的系统的指数的稳定性。

简介：为为非线性的系统的适应基于观察员的差错估计的一条途径被建议。H无穷理论被用于分析设计方法和适应观察员，系统状态和差错能从被估计的稳定的条件。差错估计错误与给定的H无穷磁道性能索引有关，这被证明，以及差错和非线性的条款的Lipschitz常数评价到变化。适应观察员的设计步被建议。甚至当系统包括非线性的条款时，模拟结果证明观察员为差错估计有好性能，它证实方法的有效性。

简介：基于的活跃颤动灵活冗余的操纵者控制的神经网络上的调查被进行。操纵者的聪明的连接与到哪个是依附的piezoceramic致动器和紧张计量器传感器的灵活连接被综合。Anonlinear适应控制策略把神经网络称为基于的间接适应控制(NNIAC)被采用改进操纵者的动态性能。the4分层的动态周期性的神经网络(DRNN)的数学模型被介绍。展示DRNN拓扑学的neuro标识符和theneuro控制器被设计离开线以便提高NNIAC的起始的坚韧性。由或者调整neuro标识符和neuro控制器，操纵者为完成需要的动态表演在线上被控制。最后，平面3R有一个聪明的连接的冗余的操纵者作为一个解说性的例子被利用。Thesimulation结果证明了控制策略的有效性。

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

简介：以便改进传播精确性和在事情(IoT)的因特网察觉到并且激活信号的效率并且保证系统稳定性，一个适应资源分配算法被建议，它动态地根据他们的信号频率域特征在部件之中分配网络带宽和优先级。一遥远察觉到并且控制无人的地面的车辆(UGV)路径追踪试验台被开发，追踪错误信号的多重UGV为表演评估在模拟被测量。与一样的网络带宽限制，建议算法能减少的结果表演积累并且UGV路径与常规静态的算法相比在超过60%追踪的最大的错误。

简介：Apairofmultichannelrecursiveleastsquares(RLS)adaptivelatticealgorithmsbasedontheorderrecursiveoflatticefiltersandthesuperiornumericalpropertiesofGivensalgorithmsisderivedinthispaper.ThederivationofthefirstalgorithmisbasedonQRdecompositionoftheinputdatamatrixdirectly,andtheGivensrotationsapproachisusedtocomputetheQRdecomposition.UsingfirstaprerotationoftheinputdatamatrixandthenarepetitionofthesinglechannelGivenslatticealgorithm,thesecondalgorithmcanbeobtained.Bothalgorithmshavesuperiornumericalproperties,particularlytherobustnesstowordlengthlimitations.Theparametervectortobeestimatedcanbeextracteddirectlyfrominternalvariablesinthepresentalgorithmswithoutabacksolveoperationwithanextratriangulararray.Theresultsofcomputersimulationoftheparameteridentificationofatwo-channelsystemarepresentedtoconfirmefficientlythederivation.

简介：Duetolowparametersensitivityforbalancedrealizations,balancedstructurebecomesagoodcandidateforanstatespaceadaptiveinfiniteimpluseresponse(MR)filter.Here,usingcoefficientsofthetransferfunctionastheadaptivefilteringparameters,abalancedadaptiveIIRfilteringalgorithmisproposedforoutput-errorminimization.ThealgorithmintheinternallybalancedrealizationguaranteesthattheadaptiveIIRfilteralwaysminimizestheratioofmaximum-to-minimumeigenvalueoftheGrammianmatricesattheeachiteration.Simulationresultsareprovidedtocorroboratetheproposedalgorithm.

简介：Inthispaper,ablockwiseadaptivesubcarrierallocationalgorithmformultiuserOrthogonalFrequencyDivisionMultiplexing(OFDM)systemisintroduced.Assumingtheknowledgeofchannelinformationforallusers,thealgorithmminimizesthetotaltransmitpowerwhilesatisfyingthetotalpowerandusers'rateconstraints.TheresultofsimulationshowsthattheproposedalgorithmreducestheaveragebitSignal-to-NoiseRatio(SNR)byapproximately4dBcomparedwithOFDM-FrequencyDivisionMultipleAccess(OFDM-FDMA),andsupportsmoreusersinamultiuserRayleighfadingchannel.Asassigningsubcarriersinblock,thecomputationalcomplexityofthealgorithmismuchlowerthanthatofthederivationof"water-filling"algorithm.

简介：Inthispaper,weconsiderthesynchronizationofchaoticHindmarshRose(HR)neuronsviaascalarcontrolinput.ChaoticHRneuronscoupledwithagapjunctionaretakenintoconsideration,andanactivecompensationmechanism-basedadaptivecontrolisemployedtorealizethesynchronizationoftwoHRneurons.Assuchanadaptivecontrolisutilized,anaccuratemodelofthesystemisofnonecessity.AsymptoticalsynchronizationoftwoHRneuronsisguaranteedbytheoreticalresults.Numericalresultsarealsoprovidedtoconfirmtheproposedsynchronizationapproach.

简介：这份报纸处理与控制不了的不稳定的linearization为非线性的系统的一个类调遣controlproblems的适应实际输出。设计一个光滑的适应调遣控制器解决几何、动态的任务withan的objectiveis任意的小稳定的追踪错误。增加一个力量综合者和robustrecursive设计技术的方法被采用强迫系统产量追踪一条需要的路径和makethe追踪速度沿着路径跟随需要的速度。一个例子被考虑，simulationresults被给。建议设计过程能被这个例子的使用说明。

简介：Inthispaper,anenergyefficientbandwidthallocationschemeisproposedforwirelesscommunicationsystems.Anoptimalbandwidthexpansion(OBE)schemeisproposedtoassigntheavailablesystembandwidthforusers.Whenthesystembandwidthdoesnotreachthefullload,theremainingbandwidthcanbeenergy-efficientlyassignedtotheotherusers.SimulationresultsshowthattheenergyefficiencyoftheproposedOBEschemeoutperformsthetraditionalsamebandwidthexpansion(SBE)scheme.Thus,theproposedOBEcaneffectivelyassignthesystembandwidthandimproveenergyefficiency.

简介：Thehighresolutionradartargetdetectionisaddressedinthenon-Gaussianclutter.Anadaptivedetectorisderivedforrange-spreadtargetbasedonanovelcovariancematrixestimator.Itisprovedthatthenewdetectorisconstantfalsealarmrate(CFAR)tobothofthecluttercovariancematrixstructureandpowerleveltheoreticallyformatchcases.ThesimulationresultsshowthatthenewdetectorisalmostCFARformismatchcases,anditoutperformstheexistingadaptivedetectorbasedonthesamplecovariancematrix.Italsoshowsthatthedetectionperformanceimproves,asthenumberofpulses,thenumberofsecondarydataortheclutterspikeincreases.Inaddition,thederiveddetectorisrobusttodifferentsubsets,estimatedcluttergroupsizesandcorrelationsofclutter.Importantly,thenumberofiterationsforpracticalapplicationisjustone.