Matlab的神经网络工具箱入门

Matlab的神经网络工具箱入门在commandwindow中键入helpnnet>>helpnnetNeuralNetworkToolboxVersion7.0(R2023b)03-Aug-2023神经网络工具箱版本7.0〔R2023b〕03八月，2023图形用户界面功能。nnstart-神经网络启动GUInctool-神经网络分类工具nftool-神经网络的拟合工具nntraintool-神经网络的训练工具nprtool-神经网络模式识别工具ntstool-NFTool神经网络时间序列的工具nntool-神经网络工具箱的图形用户界面。查看-查看一个神经网络。网络的建立功能。cascadeforwardnet-串级，前馈神经网络。competlayer-竞争神经层。distdelaynet-分布时滞的神经网络。elmannet-Elman神经网络。feedforwardnet-前馈神经网络。fitnet-函数拟合神经网络。layrecnet-分层递归神经网络。linearlayer-线性神经层。lvqnet-学习矢量量化〔LVQ〕神经网络。narnet-非线性自结合的时间序列网络。narxnet-非线性自结合的时间序列与外部输入网络。newgrnn-设计一个广义回归神经网络。newhop-建立经常性的Hopfield网络。newlind-设计一个线性层。newpnn-设计概率神经网络。newrb-径向基网络设计。newrbe-设计一个确切的径向基网络。patternnet-神经网络模式识别。感知-感知。selforgmap-自组织特征映射。timedelaynet-时滞神经网络。利用网络。网络-创立一个自定义神经网络。SIM卡-模拟一个神经网络。初始化-初始化一个神经网络。适应-允许一个神经网络来适应。火车-火车的神经网络。DISP键-显示一个神经网络的属性。显示-显示的名称和神经网络属性adddelay-添加延迟神经网络的反响。closeloop-神经网络的开放反响转换到关闭反响回路。formwb-表格偏见和成单个向量的权重。getwb-将它作为一个单一向量中的所有网络权值和偏差。noloop-删除神经网络的开放和关闭反响回路。开环-转换神经网络反响，翻开封闭的反响循环。removedelay-删除延迟神经网络的反响。separatewb-独立的偏见和重量/偏置向量的权重。setwb-将所有与单个矢量网络权值和偏差。Simulink的支持。gensim-生成Simulink模块来模拟神经网络。setsiminit-集神经网络的Simulink模块的初始条件getsiminit-获取神经网络Simulink模块的初始条件神经元-神经网络Simulink的模块库。培训职能。trainb-批具有重量与偏见学习规那么的培训。trainbfg-的BFGS拟牛顿倒传递。trainbr-贝叶斯规那么的BP算法。trainbu-与重量与偏见一批无监督学习规那么的培训。trainbuwb-与体重无监督学习规那么与偏见一批培训。trainc-循环顺序重量/偏见的培训。traincgb-共轭鲍威尔比尔重新启动梯度反向传播。traincgf-共轭弗莱彻-里夫斯更新梯度反向传播。traincgp-共轭波拉克-Ribiere更新梯度反向传播。traingd-梯度下降反向传播。traingda-具有自适应LR的反向传播梯度下降。traingdm-与动量梯度下降。traingdx-梯度下降瓦特/惯性与自适应LR的反向传播。trainlm-采用Levenberg-马奎德倒传递。trainoss-一步割线倒传递。trainr-随机重量/偏见的培训。trainrp-RPROP反向传播。trainru-无监督随机重量/偏见的培训。火车-顺序重量/偏见的培训。trainscg-规模化共轭梯度BP算法。绘图功能。plotconfusion-图分类混淆矩阵。ploterrcorr-误差自相关时间序列图。ploterrhist-绘制误差直方图。plotfit-绘图功能适合。plotinerrcorr-图输入错误的时间序列的互相关。plotperform-小区网络性能。plotregression-线性回归情节。plotresponse-动态网络图的时间序列响应。plotroc-绘制受试者工作特征。plotsomhits-小区自组织图来样打。plotsomnc-小区自组织映射邻居的连接。plotsomnd-小区自组织映射邻居的距离。plotsomplanes-小区自组织映射重量的飞机。plotsompos-小区自组织映射重量立场。plotsomtop-小区自组织映射的拓扑结构。plottrainstate-情节训练状态值。plotwb-图寒春重量和偏差值图。列出其他神经网络实现的功能。nnadapt-适应职能。nnderivati??ve-衍生功能。nndistance-距离函数。nndivision-除功能。nninitlayer-初始化层功能。nninitnetwork-初始化网络功能。nninitweight-初始化权函数。nnlearn-学习功能。nnnetinput-净输入功能。nnperformance-性能的功能。nnprocess-处理功能。nnsearch-线搜索功能。nntopology-拓扑结构的功能。nntransfer-传递函数。nnweight-重量的功能。示威，数据集和其他资源nndemos-神经网络工具箱的示威。nndatasets-神经网络工具箱的数据集。nntextdemos-神经网络设计教科书的示威。nntextbook-神经网络设计教科书的资讯。用他给出的命令nntool〔同样是在commandwindow键入〕调出图形用户界面如下>>helpnnetNeuralNetworkToolbox神经网络工具箱Version8.1(R2023b)08-Aug-20232023的8.1版Graphicaluserinterfacefunctions.图形用户界面函数nnstart-NeuralNetworkStartGUI神经网络启动图形用户界面GUInctool-Neuralnetworkclassificationtool神经网络分类工具nftool-NeuralNetworkFittingTool神经网络拟合工具nntraintool-Neuralnetworktrainingtool神经网络训练工具nprtool-Neuralnetworkpatternrecognitiontool神经网络模式识别工具ntstool-NFToolNeuralNetworkTimeSeriesToolNFTool神经网络时间序列工具nntool-NeuralNetworkToolboxgraphicaluserinterface.神经网络工具箱图形用户界面view-Viewaneuralnetwork.查看一个神经网络Networkcreationfunctions.网络生成函数cascadeforwardnet–Cascade-forwardneuralnetwork.级联神经网络competlayer-Competitiveneurallayer.竞争神经层distdelaynet-Distributeddelayneuralnetwork.分布式延迟神经网络elmannet-Elmanneuralnetwork.Elman神经网络feedforwardnet-Feed-forwardneuralnetwork.前馈神经网络fitnet-Functionfittingneuralnetwork.函数拟合神经网络layrecnet-Layeredrecurrentneuralnetwork.分层递归神经网络linearlayer-Linearneurallayer.线性神经层lvqnet-Learningvectorquantization(LVQ)neuralnetwork.学习向量量化(LVQ)神经网络narnet-Nonlinearauto-associativetime-seriesnetwork.非线性自动组合时间序列网络narxnet-Nonlinearauto-associativetime-seriesnetworkwithexternalinput.具有外部输入的非线性自动组合时间序列网络newgrnn-Designageneralizedregressionneuralnetwork.设计一个广义回归神经网络newhop-CreateaHopfieldrecurrentnetwork.创立一个Hopfield复发性网络newlind-Designalinearlayer.设计一个线性层newpnn-Designaprobabilisticneuralnetwork.设计一个概率神经网络newrb-Designaradialbasisnetwork.设计一个径向基网络newrbe-Designanexactradialbasisnetwork.设计一个精确的径向基网络patternnet-Patternrecognitionneuralnetwork.模式识别神经网络perceptron-Perceptron.selforgmap-Self-organizingmap.自组织映射timedelaynet-Time-delayneuralnetwork.时间延迟神经网络Usingnetworks.网络使用network-Createacustomneuralnetwork.创立一个定制的神经网络sim-Simulateaneuralnetwork.模拟神经网络init-Initializeaneuralnetwork.初始化一个神经网络adapt-Allowaneuralnetworktoadapt.神经网络的适应train-Trainaneuralnetwork.训练一个神经网络disp-Displayaneuralnetwork'sproperties.显示一个神经网络的属性display-Displaythenameandpropertiesofaneuralnetwork显示一个神经网络的名字和属性adddelay-Addadelaytoaneuralnetwork'sresponse.加一个延时到神经网络响应closeloop-Convertneuralnetworkopenfeedbacktoclosedfeedbackloops.转变神经网络翻开反响到关闭反响的回路formwb-Formbiasandweightsintosinglevector.使偏差和权重成为单一向量getwb-Getallnetworkweightandbiasvaluesasasinglevector.获得全部网络权重和偏差当作单一向量noloop-Removeneuralnetworkopenandclosedfeedbackloops.移去神经网络翻开和关闭反响回路openloop-Convertneuralnetworkclosedfeedbacktoopenfeedbackloops.转变神经网络关闭反响到翻开反响的回路removedelay-Removeadelaytoaneuralnetwork'sresponse.为神经网络反响移去一个延迟separatewb-Separatebiasesandweightsfromaweight/biasvector.从一个权重/偏差向量别离偏差和权重setwb-Setallnetworkweightandbiasvalueswithasinglevector.用一个单一向量设置全部网络权重和偏差值Simulinksupport.仿真支持gensim-GenerateaSimulinkblocktosimulateaneuralnetwork.生成Simulink模块来模拟神经网络setsiminit-SetneuralnetworkSimulinkblockinitialconditions设置神经网络Simulink模块初始条件getsiminit-GetneuralnetworkSimulinkblockinitialconditions获得神经网络Simulink模块初始条件neural-NeuralnetworkSimulinkblockset.神经网络Simulink模块集Trainingfunctions.训练函数trainb-Batchtrainingwithweight&biaslearningrules.批处理具有权重和偏差学习规那么的训练trainbfg-BFGSquasi-Newtonbackpropagation.BFGS拟牛顿反向传播trainbr-BayesianRegulationbackpropagation.贝叶斯规那么的反向传播trainbu-Unsupervisedbatchtrainingwithweight&biaslearningrules.无监管的批处理具有权重和偏差学习规那么的训练trainbuwb-Unsupervisedbatchtrainingwithweight&biaslearningrules.无监管的批处理具有权重和偏差学习规那么的训练trainc-Cyclicalorderweight/biastraining.循环顺序权重和偏差训练traincgb-ConjugategradientbackpropagationwithPowell-Bealerestarts.具有Powell-Beale重新开始的共轭梯度反向传播traincgf-ConjugategradientbackpropagationwithFletcher-Reevesupdates.具有Fletcher-Reeves更新的共轭梯度反向传播traincgp-ConjugategradientbackpropagationwithPolak-Ribiereupdates.具有Polak-Ribiere更新的共轭梯度Polak-Ribieretraingd-Gradientdescentbackpropagation.梯度下降反向传播traingda-Gradientdescentwithadaptivelrbackpropagation.具有自适应LR的反向传播梯度下降traingdm-Gradientdescentwithmomentum.具有动量的梯度下降traingdx-Gradientdescentw/momentum&adaptivelrbackpropagation.梯度下降瓦特/动量与自适应LR的反向传播trainlm-Levenberg-Marquardtbackpropagation.Levenberg-Marquardt反向传播trainoss-Onestepsecantbackpropagation.一步割线反向传播trainr-Randomorderweight/biastraining.随机权重/偏差训练trainrp-RPROPbackpropagation.RPROP反向传播trainru-Unsupervisedrandomorderweight/biastraining.无监管随机权重/偏差训练trains-Sequentialorderweight/biastraining.顺序权重/偏差训练trainscg-Scaledconjugategradientbackpropagation.规模化共轭梯度反向传播Plottingfunctions.绘图函数plotconfusion-Plotclassificationconfusionmatrix.图分类混淆矩阵ploterrcorr-Plotautocorrelationoferrortimeseries.误差自相关时间序列图ploterrhist-Ploterrorhistogram.误差直方图plotfit-Plotfunctionfit.绘图功能(函数)配合plotinerrcorr-Plotinputtoerrortimeseriescross-correlation.绘制输入误差时间序列互相关plotperform-Plotnetworkperformance.绘制网络性能plotregression-Plotlinearregression.绘制线性回归plotresponse-Plotdynamicnetworktime-seriesresponse.绘制动态网络时间序列反响plotroc-Plotreceiveroperatingcharacteristic.绘制接收器操作特性plotsomhits-Plotself-organizingmapsamplehits.绘制自组织映射样本采样数plotsomnc-PlotSelf-organizingmapneighborconnections.绘制自组织映射邻居关系plotsomnd-PlotSelf-organizingmapneighbordistances.绘制自组织映射邻居距离plotsomplanes-Plotself-organizingmapweightplanes.绘制自组织映射权重位面plotsompos-Plotself-organizingmapweightpositions.绘制自组织映射权重位置plotsomtop-Plotself-organizingmaptopology.绘制自组织映射拓扑结构plottrainstate-Plottrainingstatevalues.绘制训练状态值plotwb-PlotHintondiagramsofweightandbiasvalues.绘制权重和偏差值得Hinton图Listsofotherneuralnetworkimplementationfunctions.神经网络其他重要函数的列表nnadapt-Adaptfunctions.适应函数adaptwb-Sequentialorderincrementaltrainingw/learningfunctions.nnderivative-Derivativefunctions.派生(衍生)函数NeuralNetworkToolboxCalculationFunctions.神经网络工具箱计算函数Thecontentsofthisdirectorymaychangewithoutnotice.Thesefilesareimplementationfilesnotintendedfordirectuse.这个目录的内容可以改变故没有公告，这些文件是安装启用文件并非直接可应用的。nndistance-Distancefunctions.距离函数boxdist-Boxdistancefunction.Box距离函数dist-Euclideandistanceweightfunction.欧几里得距离权值函数linkdist-Linkdistancefunction.Link距离函数mandist-Manhattandistancefunction.Manhattan距离函数nndivision-Divisionfunctions.除法函数divideblock-Partitionindicesintothreesetsusingblocksofindices.划分指标成为三个可用指标块集divideind-Partitionindicesintothreesetsusingspecifiedindices.划分指标成为三个可用指定指标集divideint-Partitionindicesintothreesetsusinginterleavedindices.划分指标成为三个可用交叉存储指标集dividerand-Partitionindicesintothreesetsusingrandomindices.划分指标成为三个可用随机指标集dividetrain-Partitionindicesintotrainingsetonly.划分指标仅成为训练集nninitlayer-Initializelayerfunctions.初始化层函数initnw-Nguyen-Widrowlayerinitializationfunction.Nguyen-Widrow层初始化函数initwb-By-weight-and-biaslayerinitializationfunction.附近(次要的)-权值和阈值层初始化函数nninitnetwork-Initializenetworkfunctions.初始化网络函数initlay-Layer-by-layernetworkinitializationfunction.叠层网络初始化函数nninitweight-Initializeweightfunctions.初始化权值函数Biasonlyinitializationfunctions仅阈值初始化函数initcon-Consciencebiasinitializationfunction.Conscience阈值初始化函数nnlearn-Learningfunctions.学习函数learncon-Consciencebiaslearningfunction.Conscience阈值学习函数learngd-Gradientdescentweight/biaslearningfunction.梯度下降权值/阈值学习函数learngdm-Gradientdescentw/momentumweight/biaslearningfunction.梯度下降w/动量权值/阈值学习函数learnh-Hebbweightlearningrule.Hebb权值学习规那么learnhd-Hebbwithdecayweightlearningrule.有衰减Hebb权值学习规那么learnis-Instarweightlearningfunction.Instar权值学习函数learnk-Kohonenweightlearningfunction.Kohonen权值学习函数learnlv1-LVQ1weightlearningfunction.LVQ1权值学习函数learnlv2-LVQ2.1weightlearningfunction.LVQ2.1权值学习函数learnos-Outstarweightlearningfunction.Outstar权值学习函数learnp-Perceptronweight/biaslearningfunction.感知器的权值/偏差学习函数learnpn-Normalizedperceptronweight/biaslearningfunction.标准感知器的学习函数learnsom-Self-organizingmapweightlearningfunction.自组织映射权值学习函数learnsomb-LEARNSOMBatchself-organizingmapweightlearningfunction.LEARNSOM批处理自组织映射权值学习函数learnwh-Widrow-Hoffweight/biaslearningfunction.Widrow-Hoff权值/偏差学习函数nnnetinput-Netinputfunctions.网络输入函数netprod-Productnetinputfunction.Product网络输入函数netsum-Sumnetinputfunction.Sum网络输入函数nnperformance-Performancefunctions.性能函数mae-Meanabsoluteerrorperformancefunction.平均绝对误差性能函数mse-Meansquarederrorperformancefunction.均方误差性能函数sae-Sumabsoluteerrorperformancefunction.Sum绝对误差性能函数sse-Sumsquarederrorperformancefunction.Sum均方误差性能函数nnprocess-Processingfunctions.处理函数GeneralDataPreprocessing一般数据预处理fixunknowns-Processesmatrixrowswithunknownvalues.用未知值处理矩阵行mapminmax-Mapmatrixrowminimumandmaximumvaluesto[-11].映射矩阵行最小和最大值成[-1,1]mapstd-Mapmatrixrowmeansanddeviationstostandardvalues.映射矩阵行均值和偏差成标准值processpca-Processesrowsofmatrixwithprincipalcomponentanalysis.用主成分分析处理矩阵行removeconstantrows-Removematrixrowswithconstantvalues.用常量移去矩阵行removerows-Removematrixrowswithspecifiedindices.用指定指标移去矩阵行DataPreprocessingforSpecificAlgorithms特定算法数据预处理lvqoutputs-DefinesettingsforLVQoutputs,withoutchangingvalues.为LVQ定义设置，没有值的改变nnsearch-Linesearchfunctions.线性搜索函数srchbac-One-dimensionalminimizationusingbacktracking.用回溯法一维最小化srchbre-One-dimensionalintervallocationusingBrent'smethod.用Brent法一维区间位置srchcha-One-dimensionalminimizationusingthemethodofCharalambous.用Charalambous方法一维最小化srchgol-One-dimensionalminimizationusinggoldensectionsearch.用黄金分割收索一维最小化srchhyb-One-dimensionalminimizationusingahybridbisection-cubicsearch.用平分三次收索一维最小化nntopology-Topologyfunctions.拓扑函数gridtop-Gridlayertopologyfunction.网格层拓扑函数hextop-Hexagonallayertopologyfunction.六角形层拓扑函数randtop-Randomlayertopologyfunction.随机层拓扑函数tritop-Trianglelayertopologyfunction.三角形层拓扑函数nntransfer-Transferfunctions.传递函数compet-Competitivetransferfunction.竞争传递函数elliotsig-Elliotsigmoidtransferfunction.ElliotS型传递函数hardlim-Positivehardlimittransferfunction.正的硬界限传递函数ha