Neuromorphic Devices for Brain-inspired Computing: Artificial Intelligence, Perception, and Robotics

259 Pages·2022·8.924 MB·English

by  Qing Wan, Yi Shi

NeuromorphicDevicesforBrain-InspiredComputing

Neuromorphic Devices for Brain-Inspired
Computing
Artificial Intelligence, Perception, and Robotics
Edited by Qing Wan and Yi Shi
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v
Contents
Preface xi
1 Two-TerminalNeuromorphicMemristors 1
Hui-KaiHe,He-MingHuang,andRuiYang
1.1 MemristiveDevices 1
1.1.1 MemristiveDeviceStructureandMaterials 1
1.1.1.1 MemristiveDeviceStructure 1
1.1.1.2 MemristiveMaterials 2
1.1.2 ResistiveSwitchingBehavior 4
1.1.2.1 VolatileResistiveSwitching 5
1.1.2.2 NonvolatileResistiveSwitching 7
1.2 ResistiveSwitchingMechanisms 7
1.2.1 Filamentary-TypeResistiveSwitching 8
1.2.1.1 CationMigration-RelatedFilaments 8
1.2.1.2 AnionMigration-RelatedFilaments 11
1.2.2 Interface-TypeResistiveSwitching 14
1.3 MemristiveBioinspiredDevices 17
1.3.1 MemristiveSynapses 18
1.3.1.1 Short-TermMemristiveSynapses 20
1.3.1.2 Long-TermMemristiveSynapses 23
1.3.2 MemristiveNeurons 27
1.3.2.1 BioplausibleMemristiveNeurons 31
1.3.2.2 BiophysicalMemristiveNeurons 34
1.4 MemristiveNeuralNetworks 36
1.4.1 MemristiveANNComputing 36
1.4.2 MemristiveSNNComputing 39
1.5 SummaryandOutlook 41
References 42
2 SpintronicNeuromorphicDevices 47
DemingZhang,SaiLi,XinranWang,AoDu,WangKang,LangZeng,and
WeishengZhao
2.1 Introduction 47
2.2 MagneticTunnelJunctionforNeuromorphicComputing 48
vi Contents
2.2.1 DeviceStructureandtheWrite/ReadOperation 48
2.2.1.1 BinaryMagneticTunnelJunction 48
2.2.1.2 Multi-levelSpintronicMemristor 49
2.2.2 WorkingastheSynapticDevice 51
2.2.2.1 StochasticBinarySynapticDevice 51
2.2.2.2 Analog-LikeSynapticDevice 52
2.2.3 WorkingastheNeuralDevice 54
2.2.3.1 SpikingNeuralDevice 54
2.2.3.2 ArtificialNeuralDevice 57
2.2.4 All-SpinNeuralNetwork 61
2.2.4.1 All-SpinArtificialNeuralNetworkwithCompoundScheme 61
2.2.4.2 All-SpinSpikingNeuralNetworkwithSpintronicMemristor 62
2.2.5 SummaryandOutlook 62
2.3 Skyrmion-BasedNeuromorphicComputing 62
2.3.1 TheIntroductionofSkyrmions 62
2.3.2 Skyrmion-BasedSynapseDevices 64
2.3.3 Skyrmion-BasedNeuronDevices 65
2.3.4 Skyrmion-BasedReservoirComputing 67
2.3.5 Skyrmion-BasedStochasticComputing 68
2.3.6 ChallengesandPerspectives 69
2.4 SpinTorqueOscillatorsforNeuromorphicComputing 72
2.4.1 IntroductiontoSpinTorqueOscillator 72
2.4.2 AssociativeMemoryBasedonInjectionLockingofSTO 73
2.4.3 ReservoirComputingBasedonSTO 74
2.4.4 RecurrentNeuralNetworkbasedonDelayedFeedbackofSTO 75
2.4.5 NeuromorphicComputingBasedontheSynchronizationofSTO 77
2.4.6 ProblemsandPerspectives 77
2.5 ConclusionandOutlook 80
References 80
3 MultiterminalNeuromorphicDeviceswithCognitive
Behaviors 91
LiQiangZhu,JiaChengCai,ZhengYuRen,WenXiong,andQingWan
3.1 Introduction 91
3.2 MultiterminalNeuromorphicMemristors 92
3.2.1 Memristor-BasedNeuromorphicDevices 92
3.2.2 MultiterminalMemristorforNeuromorphicSystem 96
3.2.2.1 SynapticCompetitionandCooperationonMultiterminalMemristor 96
3.2.2.2 HeterosynapticPlasticityonMultiterminalMemristor 97
3.2.2.3 MultiterminalMemtransistor 98
3.3 MultiterminalNeuromorphicTransistors 99
3.3.1 NeuronTransistors 99
3.3.2 NeuromorphicDevicesforChemicalBiosensorApplications 101
3.3.2.1 ChemicalBiosensors 101
3.3.2.2 NeuronTransistorsforChemicalBiosensor 102
Contents vii
3.3.2.3 Multi-gateNeuromorphicTransistorforpHSensor 103
3.3.3 DendriticAlgorithmonMultiterminalNeuromorphicTransistors 103
3.3.3.1 EGT-BasedNeuromorphicTransistors 103
3.3.3.2 Multi-gateNeuromorphicTransistor 105
3.3.3.3 DendriteNeuronandDendriticAlgorithm 106
3.3.3.4 Multi-gateNeuromorphicTransistorforPatternRecognition 109
3.4 NeuromorphicTransistorsforPerceptionLearningActivities 109
3.4.1 ArtificialTactileDevice 109
3.4.2 ArtificialVisionDevice 112
3.4.3 ArtificialAuditoryDevice 113
3.5 ConclusionandOutlook 114
Acknowledgments 116
References 116
4 NeuromorphicDevicesBasedonChalcogenideMaterials 125
JiaChen,YifanLu,ZheYang,YiLi,andXiangshuiMiao
4.1 Introduction 125
4.2 OvonicMemorySwitching(OMS)andThresholdSwitching(OTS)in
ChalcogenideMaterials 126
4.3 ArtificialSynapsesBasedonMSBehaviors 129
4.4 ArtificialNeuronsBasedonTSEffects 136
4.5 HardwareNeuralNetworks 139
4.6 SummaryandOutlook 143
References 144
5 NeuromorphicDevicesBasedonOrganicMaterials 149
JunyaoZhangandJiaHuang
5.1 Introduction 149
5.2 Two-TerminalOrganicNeuromorphicDevices 149
5.2.1 MetalFilamentConducting-BasedMemristors 150
5.2.2 RedoxReaction-BasedMemristors 152
5.2.3 IonMigration-BasedMemristors 153
5.2.4 ChargeTrapping-BasedMemristors 155
5.3 Three-TerminalOrganicNeuromorphicDevices 157
5.3.1 Floating-GateTransistors 157
5.3.2 Electrolyte-GateTransistors 158
5.3.3 Ferroelectric-GateTransistors 162
5.3.4 OptoelectronicTransistors 164
5.4 InnovativeApplicationsofOrganicNeuromorphicDevicesforBionic
PerceptionSystems 165
5.4.1 ArtificialVisualizationSystems 166
5.4.2 Tactile-PerceptionSystems 167
5.5 SummaryandOutlook 169
References 170
viii Contents
6 NeuromorphicComputingSystemswithEmerging
Devices 173
QiumengWei,JianshiTang,BinGao,XinyiLi,HeQian,andHuaqiangWu
6.1 Introduction 173
6.1.1 BackgroundIntroduction 173
6.1.2 TheMotivationforNeuromorphicComputing 174
6.1.3 ProgressandChallengesofCMOS-BasedNeuromorphic
Computing 174
6.1.4 PrinciplesofMemristors 176
6.2 DNNsBasedonSynapticDevices 178
6.2.1 DevicePerformanceRequirements 178
6.2.2 ArrayDemonstrations 179
6.2.3 ChipandSystemImplementations 183
6.2.4 ArchitectureandAlgorithmOptimization 185
6.2.4.1 Quantization 185
6.2.4.2 NonidealAnalogSwitchingCharacteristics 186
6.2.4.3 SynapticArraySize 186
6.3 SNNsBasedonNeuromorphicDevices 187
6.3.1 LearningRulesandMemoryPrinciples 188
6.3.1.1 SynapsesandNeuronsinSNNs 188
6.3.1.2 LearningAlgorithmsandBenchmarksforSNNs 188
6.3.2 SNNswithSynapticDevicesandNeuronalDevices 189
6.3.2.1 SynapticDeviceswithPlasticity 189
6.3.2.2 NeuronalDevices 191
6.3.3 SNNImplementationswithSynapticArrays 192
6.4 OtherNeuromorphicSystems 196
6.4.1 HyperdimensionalComputing 196
6.4.2 DendriticComputing 196
6.4.3 ReservoirComputing 202
6.4.4 OscillatoryNeuralNetwork 203
6.4.5 HopfieldNeuralNetworkandSimulatedAnnealing 203
6.5 SummaryandOutlook 204
References 206
7 NeuromorphicPerceptualSystemswithEmerging
Devices 217
YingZhu,ChangjinWan,andQingWan
7.1 Background 217
7.2 SensationandPerception 218
7.2.1 FromSensationtoPerception 218
7.2.2 PursingArtificialPerceptionbyNeuromorphicDevices 219
7.3 ImplementationofArtificialPerception 221
7.3.1 BuildingBlockofArtificialPerception:ArtificialSensoryNeuron 221
7.3.2 IntelligentTasksBasedonArtificialPerception 223
7.3.2.1 PatternRecognitionTasks 224