简介：建立行之有效的现代中药复方研究体系,是中医药现代化进程中亟待解决的关键问题之一。本文遵循系统论和还原论相结合、宏观与微观研究相结合、体内研究和体外研究相结合的原则,以系统生物学与网络生物学作为主要技术支撑,尝试提出包括化学物质基础研究、现代药理学研究、系统生物学和网络生物学研究在内的现代中药复方研究体系,并结合中药复方的具体研究实例,对该研究体系指导下的中药复方现代化研究进行了初步探讨。本文提出的复方研究体系为中药复方的现代研究提供了方法论,将有助于系统、深刻地揭示中药复方的科学内涵,指导中药复方新药研发,更好地传承和发展中医药理论。

简介：

简介：Dynamicnodecreationandfastlearningalgorithmforahybridfeedforwardneuralnetwork.Flight-pathanglecontrolvianeuro-adaptiveBackstepping.Locallearningframeworkforhandwrittencharacterrecognition.Maximizingmarginsofmultilayerneuralnetworks.ModularnetworkSOMself-orgmlizingmapofasystemsgroupinfunctionspace.

简介：

简介：

简介：ApplicationoftheRTNNmodelforasystemidentification,predictionandcontrol；AssociativeMemoryUsingRatioRuleforMulti-valuedPatternAssociation；Batch-to-BatchModel-basedIterativeOptimisationControlforaBatchPolymerisationReactor；BehaviouralPlasticityinAutonomousAgents:AComparisonbetweenTwoTypesofController；ChannelEqualizationUsingComplex-ValuedRecurrentNeuralNetworks；Classificationofnaturallanguagesentencesusingneuralnetworks；Combiningarecurrentneuralnetworkandtheoutputregulationtheoryfornon-linearadaptivecontrol。

简介：

简介：ConfigurablemultilayerCNN-UMemulatoronFPGA；Cortically-inspiredVisualProcessingwithaFourLayerCellularNeuralNetwork；Effectofcouplingresistorsonsteadypatternsincoupledoscillatornetworks；Exponentialconvergenceestimatesforneuralnetworkswithmultipledelays；FEATUREEXTRACTIONINEPILEPSYUSINGACELLULARNEURALNETWORKBASEDDEVICEFIRSTRESULTS；FurtherResultsontheStabilityofDelayedCellularNeuralNetworks；Globalstabilityanalysisindelayedcellularneuralnetworks；ImageedgedetectionusingadaptivemorphologyMeyerWavelet-CNN。

简介：

简介：PredictionoftheDimensionalChangesduringSinteringusingBackpropagationAlgorithm，Predictionofthenextstockpriceusingneuralnetwork-extractionthefeaturetopredictnextstockpricebyfiltering，Pulsemodeneuronwithpiecewiselinearactivationfunction，Remarksonmultilayerneuralnetworksinvolvingchaosneurons……

简介：

简介：人工神经网络是另外一种计算模式。冯·诺依曼机器是以．人类信息处理过程的处理/记忆的抽象为基础的，而神经网络是以动物大脑并行处理的体系结构为基础的。这是一种多处理器的计算机系统，由大量简单的处理单元高度互连，简单分级通信，以及在各单元之间进行适应性交互作用组成。

简介：

简介：

简介：AnewapproachtogenerateAself-organizingfuzzyneuralnetworkmodel.Anonlinearcombiningforecastmethodbasedonfuzzyneuralnetwork.Anovelclustermethodinfrizzyneuralnetworks.AnovelrobustPIDcontrollerdesignbyfuzzyneuralnetwork.Arecurrentfuzzyneuralnetwork:learningandapplication.Astudyofchatterpredictioninendmillingprocess(fuzzyneuralnetworkmodelwithinputsofcuttingconditionsandsound.Aweightedfuzzyreasoninganditscorrespondingneuralnetwork.

简介：

简介：

简介：PriorityorderedBPneuralnetworkandtheapplicationforspeakeridentification；ProbingmodificationofBPneuralnetworklearning-rate；Real-timeoptimalexcitationcontrollerusingneuralnetwork；ResearchonthemodelingoftheaxialloaddistributioncoefficientofcylindricalgearsingearCADbasedonANN；Short-termsystemmarginalpriceforecastingwithhybridmodule；StudyonautomaticcreatingmethodofpublictransportationdispatchingformbasedonBPneuralnetwork。

简介：HarmonicMinimizingNeuralNetworkSVCControllerforCompensatingUnbalancedFluctuatingLoads；ImplementationofanAdaptivePredictor-CorrectorNeuralControllerwithintheNASAIFCSF-15WVUSimulator；NeuralNetworkAdaptiveControlofaSpacePlatform-BasedDeployableManipulator；Neuralnetworkcontroldesignforarigid-linkelectricallydrivenrobot；Neuralnetworkcontrolfordynamicvoltagerestorer；NeuralNetworkControlofAir-to-FuelRatioinaBi-FuelEngine；Neuralnetworkcontrolofcoldflowcirculatingfluidizedbed；Neuralnetworkcontrolofmultlvariableprocesseswithafastoptimisationalgorithm。

简介：