简介:AnExtendedParticleSwarmOptimizer(EPSO)isproposedinthispaper.Inthisnewalgorithm,notonlythelocalbutalsotheglobalbestpositionwillimpacttheparticle'svelocityupdatingprocess.EPSOisanintegrationofLocalBestparadigm(LBEST)andGlobalBestparadigm(GBEST)anditsignificantlyenhancestheperformanceoftheconventionalparticleswarmoptimizers.TheexperimentresultshaveprovedthatEPSOdeservestobeinvestigated.
简介:为了解决粒子退化现象并且同时避免,取样贫穷,这份报纸为一般大小写基于好采样算法建议了一个改进粒子过滤器,与好采样(PF-FR)作为粒子过滤器打电话。由介绍比较距离的过程并且基于优化联合计划产生新粒子,因此,PF-FR过滤器以粒子系统的有效性和差异两个都比通用采样重要性采样粒子过滤器(PF先生)更好表现在nonlinear/non-Gaussian的状态的显然改善的评价精确性当模特儿。模拟显示建议PF-FR算法能维持粒子的差异并且因此与粒子的更少的数字完成一样的评价精确性。因而,PF-FR过滤器是在非线性的州的评价的应用的一种竞争选择。
简介:这篇文章处理导致一个混合linear/non-linear模型评价问题的调遣目标追踪的问题。为调遣追踪系统,扩大了Kalman过滤器(EKF)或粒子过滤器(PF)传统地被用来估计状态。在这篇文章,排斥了粒子过滤器(MPF)处于一个混合linear/non-linear模型评价问题为申请被介绍。MPF是Kalman过滤器(KF)和PF的联合。它因此认为两个他们有利并且能被用于混合linear/non-linear基础,在有条件地线性的状态用KF被估计,非线性的状态用PF被估计的地方。模拟结果证明MPF保证评价精确性并且在调遣追踪申请的目标与PF和EKF相比减轻潜在的计算负担问题。
简介:Orthogonalfrequencydivisionmultiplexing(OFDM)whichhasbeenadoptedinthelong-termevolution(LTE)systemcanimprovethesystemcapacityobviously.However,italsobringsaboutsevereinter-cellinterference(ICI)forcell-edgeusers(CEUs).Totacklethisproblem,multi-userselectionandpowercontrol(MuS-PC)isproposedasanefficientschemeinuplinkcoordinatedmulti-pointmulti-usermulti-inputmulti-output(CoMP-MU-MIMO)transmission/reception.Thispaperjointlyconsidersuser’ssignaltointerferenceplusnoiseratio(SINR)andproportionalfairness(PF)tomaximizethetotalchannelcapacityinmulti-userselectionbyformulatingapenaltyfunction.Tosimplifythepenaltyfunction’scomputation,particleswarmoptimization(PSO)algorithmisintroduced.Inaddition,powercontrolisadoptedtomaximizeoverallenergyefficiency.SimulationresultsdemonstratethattheMuS-PCschemecannotonlyobtaintheoptimaltotalchannelcapacitywhileguaranteeeachuser’squalityofservice(QoS)andPF,butalsolargelyreducecomputationalcomplexityandimproveenergyefficiency.Asaresult,thepoorcommunicationqualityofCEUscanbeenhanced.