| 词条 | 脉冲耦合神经网络及应用 |
| 释义 | 图书信息出版社: 高等教育出版社; 第1版 (2010年6月1日) 外文书名: Applications of Pulse Coupled Neural Networks 精装: 199页 正文语种: 英语 开本: 16 ISBN: 9787040279788 条形码: 9787040279788 尺寸: 23.6 x 15.6 x 2 cm 重量: 499 g 内容简介《脉冲耦合神经网络及应用(国内英文版)》内容简介：Applications of Pulse-Coupled Neural Networks explores the fields of image processing, including image filtering, image segmentation, image fusion, image coding, image retrieval, and biometric recognition, and the role of pulse-coupled neural networks in these fields. This book is intended for researchers and graduate students in artificial intelligence, pattern recognition, electronic engineering, and computer science. 目录Chapter1 Pulse-CoupledNeuralNetworks 1.1LinkingFieldModel 1.2PCNN 1.3ModifiedPCNN 1.3.1IntersectionCorticalModel 1.3.2SpikingCorticalModel 1.3.3Multi-channelPCNN Summary References Chapter2 ImageFiltering 2.1TraditionalFilters 2.1.1MeanFilter 2.1.2MedianFilter 2.1.3MorphologicalFilter 2.1.4WienerFilter 2.2ImpulseNoiseFiltering 2.2.1DescriptionofAlgorithmⅠ 2.2.2DescriptionofAlgorithmⅡ 2.2.3ExperimentalResultsandAnalysis 2.3GaussianNoiseFiltering 2.3.1PCNNNIandTimeMatrix 2.3.2DescriptionofAlgorithmⅢ 2.3.3ExperimentalResultsandAnalysis Summary References Chapter3 ImageSegmentation 3.1TraditionalMethodsandEvaluationCriteria 3.1.1ImageSegmentationUsingArithmeticMean 3.1.2ImageSegmentationUsingEntropyandHistogram 3.1.3ImageSegmentationUsingMaximumBetween-clusterVariance 3.1.4ObjectiveEvaluationCriteria 3.2ImageSegmentationUsingPCNNandEntropy 3.3ImageSegmentationUsingSimplifiedPCNNandGA 3.3.1SimplifiedPCNNModel 3.3.2DesignofApplicationSchemeofGA 3.3.3FlowofAlgorithm 3.3.4ExperimentalResultsandAnalysis Summary References Chapter4 ImageCoding 4.1IrregularSegmentedRegionCoding 4.1.1CodingofContoursUsingChainCode 4.1.2BasicTheoriesonOrthogonality 4.1.3OrthonormalizingProcessofBasisFunctions 4.1.4ISRCCodingandDecodingFramework 4.2IrregularSegmentedRegionCodingBasedonPCNN 4.2.1SegmentationMethod 4.2.2ExperimentalResultsandAnalysis Summary References Chapter5 ImageEnhancement 5.1ImageEnhancement 5.1.1ImageEnhancementinSpatialDomain 5.1.2ImageEnhancementinFrequencyDomain 5.1.3HistogramEqualization 5.2PCNNTimeMatrix 5.2.1HumanVisualCharacteristics 5.2.2PCNNandHumanVisualCharacteristics 5.2.3PCNNTimeMatrix 5.3ModifiedPCNNModel 5.4ImageEnhancementUsingPCNNTimeMatrix 5.5ColorImageEnhancementUsingPCNN Summary References Chapter6 ImageFusion 6.1PCNNandImageFusion 6.1.IPreliminaryofImageFusion 6.1.2ApplicationsinImageFusion 6.2MedicalImageFusion 6.2.1DescriptionofModel 6.2.2ImageFusionAlgorithm 6.2.3ExperimentalResultsandAnalysis 6.3Multi-focusImageFusion 6.3.1Dual-channelPCNN 6.3.2ImageSharpnessMeasure 6.3.3PrincipleofFusionAlgorithm 6.3.4ImplementationofMulti-focusImageFusion 6.3.5ExperimentalResultsandAnalysis Summary References Chapter7 FeatureExtraction 7.1FeatureExtractionwithPCNN 7.1.1TimeSeries 7.1.2EntropySeries 7.1.3StatisticSeries 7.1.4OrthogonalTransform 7.2NoiseImageRecognition 7.2.1FeatureExtractionUsingPCNN 7.2.2ExperimentalResultsandAnalysis 7.3ImageRecognitionUsingBarycenterofHistogramVector 7.4InvariantTextureRetrieval 7.4.1TextureFeatureExtractionUsingPCNN 7.4.2ExperimentalResultsandAnalysis 7.5IrisRecognitionSystem 7.5.1IrisRecognition 7.5.2IrisFeatureExtractionUsingPCNN 7.5.3ExperimentalResultsandAnalysis Summary References Chapter8 CombinatorialOptimization 8.1ModifiedPCNNBasedonAuto-wave 8.1.1Auto-waveNatureofPCNN 8.1.2Auto-waveNeuralNetwork 8.1.3TristateCascadingPulseCoupleNeuralNetwork 8.2TheShortestPathProblem 8.2.1AlgorithmforShortestPathProblemsBasedonTCPCNN 8.2.2ExperimentalResultsandAnalysis 8.3TravelingSalesmanProblem 8.3.1AlgorithmforOptimalProblemsBasedonAWNN 8.3.2ExperimentalResultsandAnalysis Summary References Chapter9 FPGAImplementationofPCNNAlgorithm 9.1FndamentalPrincipleofPCNNHardwareImplementation 9.2AlteraDE2-70ImplementationofPCNN 9.2.1PCNNImplementationUsingAlteraDE2-70 9.2.2ExperimentalResultsandAnalysis Summary References Index |
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