neural networks for applied sciences and engineering (2006)

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1、q2006byTaylor&FrancisGroup,LLCq2006byTaylor&FrancisGroup,LLCq2006byTaylor&FrancisGroup,LLCq2006byTaylor&FrancisGroup,LLCDedicationToDonMyhusbandForyourconstantlove,support,andencouragementTodothebestIcandoinallMyendeavorsasaWomanandaScholar!q2006byTaylor&FrancisGroup,LLCq2006byT

2、aylor&FrancisGroup,LLCContentsPreface......................................................................................................xviiAcknowledgments.....................................................................................xxiAbouttheAuthor...................

3、.................................................................xxiii1FromDatatoModels:ComplexityandChallengesinUnderstandingBiological,Ecological,andNaturalSystems.................................................................................11.1:Introduction11.2:Layoutofthe

4、Book4References72FundamentalsofNeuralNetworksandModelsforLinearDataAnalysis................................................................112.1:IntroductionandOverview112.2:NeuralNetworksandTheirCapabilities122.3:InspirationsfromBiology162.4:ModelingInformationProcessinginNeuro

5、ns182.5:NeuronModelsandLearningStrategies192.5.1:ThresholdNeuronasaSimpleClassifier202.5.2:LearningModelsforNeuronsandNeuralAssemblies232.5.2.1:HebbianLearning232.5.2.2:UnsupervisedorCompetitiveLearning262.5.2.3:SupervisedLearning262.5.3:PerceptronwithSupervisedLearningasaClassifi

6、er272.5.3.1:PerceptronLearningAlgorithm282.5.3.2:APracticalExampleofPerceptrononaLargerRealisticDataSet:IdentifyingtheOriginofFishfromtheGrowth-RingDiameterofScales352.5.3.3:ComparisonofPerceptronwithLinearDiscriminantFunctionAnalysisinStatistics38q2006byTaylor&FrancisGroup,LLCv

7、iii&2.5.3.4:Multi-OutputPerceptronforMulticategoryClassification402.5.3.5:Higher-DimensionalClassificationUsingPerceptron452.5.3.6:PerceptronSummary452.5.4:LinearNeuronforLinearClassificationandPrediction462.5.4.1:LearningwiththeDeltaRule472.5.4.2:LinearNeuronasaClassifier512.5.4.3:

8、ClassificationPropertiesofaLinearNeuronasaSubset