简介:ApplicationoftheRTNNmodelforasystemidentification,predictionandcontrol;AssociativeMemoryUsingRatioRuleforMulti-valuedPatternAssociation;Batch-to-BatchModel-basedIterativeOptimisationControlforaBatchPolymerisationReactor;BehaviouralPlasticityinAutonomousAgents:AComparisonbetweenTwoTypesofController;ChannelEqualizationUsingComplex-ValuedRecurrentNeuralNetworks;Classificationofnaturallanguagesentencesusingneuralnetworks;Combiningarecurrentneuralnetworkandtheoutputregulationtheoryfornon-linearadaptivecontrol。
简介:Arecurrentlocalmodelnetworkfor,nonlinearprocessmodeling.ARECURRENTNEURALNETWORKFORI-DPHASERETRIEVAL.ARecurrentNeuralNetworkforNonlinearConvexProgramming.ArecurrentneuralnetworkmodeloftheB.T.fed-batchfermentationprocess.ActiveControlofSoundbasedonDiagonalRecurrentNeuralNetwork.
简介:Adesignmethodfornoisecancellerusingrecurrentneuralfilter,ADRNN-baseddirectmulti-stepadaptivepredictorforintelligentsystems,Agenerationalterationmodelforevolvingrecurrentneuralnetworktopologiesalongwithweights,AHIGH-PERFORMANCEMULTI-PURPOSEDSPARCHITECTUREFORSIGNALPROCESSINGRESEARCH……
简介:研究了非高斯列维噪声作用下非线性系统的渐近线性化方法和Lyapunov指数.利用渐近线性化方法将非线性系统线性化,通过系统的响应轨迹验证了该方法的有效性.通过广义的伊藤法则公式,推导出了列维噪声驱动下Lyapunov指数的一般表达式.给出当参数变化时,非线性系统的随机稳定性分析.