简介:人工神经网络是人工智能的重要分支,自其创始伊始便成为了人工智能领域的研究热点。本文从人工神经网络的发展历史开始,介绍了其在医学,信息,控制等方面的应用及其现状,对其中的优缺点进行了简要的分析。并对人工神经网络未来的发展作简要的展望。
简介:Dynamicnodecreationandfastlearningalgorithmforahybridfeedforwardneuralnetwork.Flight-pathanglecontrolvianeuro-adaptiveBackstepping.Locallearningframeworkforhandwrittencharacterrecognition.Maximizingmarginsofmultilayerneuralnetworks.ModularnetworkSOMself-orgmlizingmapofasystemsgroupinfunctionspace.
简介:ApplicationoftheRTNNmodelforasystemidentification,predictionandcontrol;AssociativeMemoryUsingRatioRuleforMulti-valuedPatternAssociation;Batch-to-BatchModel-basedIterativeOptimisationControlforaBatchPolymerisationReactor;BehaviouralPlasticityinAutonomousAgents:AComparisonbetweenTwoTypesofController;ChannelEqualizationUsingComplex-ValuedRecurrentNeuralNetworks;Classificationofnaturallanguagesentencesusingneuralnetworks;Combiningarecurrentneuralnetworkandtheoutputregulationtheoryfornon-linearadaptivecontrol。
简介:ConfigurablemultilayerCNN-UMemulatoronFPGA;Cortically-inspiredVisualProcessingwithaFourLayerCellularNeuralNetwork;Effectofcouplingresistorsonsteadypatternsincoupledoscillatornetworks;Exponentialconvergenceestimatesforneuralnetworkswithmultipledelays;FEATUREEXTRACTIONINEPILEPSYUSINGACELLULARNEURALNETWORKBASEDDEVICEFIRSTRESULTS;FurtherResultsontheStabilityofDelayedCellularNeuralNetworks;Globalstabilityanalysisindelayedcellularneuralnetworks;ImageedgedetectionusingadaptivemorphologyMeyerWavelet-CNN。
简介:PredictionoftheDimensionalChangesduringSinteringusingBackpropagationAlgorithm,Predictionofthenextstockpriceusingneuralnetwork-extractionthefeaturetopredictnextstockpricebyfiltering,Pulsemodeneuronwithpiecewiselinearactivationfunction,Remarksonmultilayerneuralnetworksinvolvingchaosneurons……
简介:AnewapproachtogenerateAself-organizingfuzzyneuralnetworkmodel.Anonlinearcombiningforecastmethodbasedonfuzzyneuralnetwork.Anovelclustermethodinfrizzyneuralnetworks.AnovelrobustPIDcontrollerdesignbyfuzzyneuralnetwork.Arecurrentfuzzyneuralnetwork:learningandapplication.Astudyofchatterpredictioninendmillingprocess(fuzzyneuralnetworkmodelwithinputsofcuttingconditionsandsound.Aweightedfuzzyreasoninganditscorrespondingneuralnetwork.