NeuralNetworksforAppliedSciencesandEngineering

NeuralNetworksforAppliedSciencesandEngineering
Inresponsetotheexponentiallyincreasingneedtoanalyzevastamountsofdata,NeuralNetworksforAppliedSciencesandEngineering:FromFundamentalstoComplexPatternRecognitionprovidesscientistswithasimplebutsystematicintroductiontoneuralnetworks.Beginningwithanintroductorydiscussionontheroleofneuralnetworksinscientificdataanalysis,thisbookprovidesasolidfoundationofbasicneuralnetworkconcepts.Itcontainsanoverviewofneuralnetworkarchitecturesforpracticaldataanalysisfollowedbyextensivestep-by-stepcoverageonlinearnetworks,aswellas,multi-layerperceptronfornonlinearpredictionandclassificationexplainingallstagesofprocessingandmodeldevelopmentillustratedthroughpracticalexamplesandcasestudies.LaterchapterspresentanextensivecoverageonSelfOrganizingMapsfornonlineardataclustering,recurrentnetworksforlinearnonlineartimeseriesforecasting,andothernetworktypessuitableforscientificdataanalysis.Withaneasytounderstandformatusingextensivegraphicalillustrationsandmultidisciplinaryscientificcontext,thisbookfillsthegapinthemarketforneuralnetworksformulti-dimensionalscientificdata,andrelatesneuralnetworkstostatistics.FeaturesxExplainsneuralnetworksinamulti-disciplinarycontextxUsesextensivegraphicalillustrationstoexplaincomplexmathematicalconceptsforquickandeasyunderstanding?Examinesin-depthneuralnetworksforlinearandnonlinearprediction,classification,clusteringandforecastingxIllustratesallstagesofmodeldevelopmentandinterpretationofresults,includingdatapreprocessing,datadimensionalityreduction,inputselection,modeldevelopmentandvalidation,modeluncertaintyassessment,sensitivityanalysesoninputs,errorsandmodelparametersSandhyaSamarasingheobtainedherMScinMechanicalEngineeringfromLumumbaUniversityinRussiaandanMSandPhDinEngineeringfromVirginiaTech,USA.