STDP and STDP variations with memristors for spiking neuromorphic learning systems.
about
Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral InhibitionAnalog Memristive Synapse in Spiking Networks Implementing Unsupervised LearningActivity-dependent synaptic plasticity of a chalcogenide electronic synapse for neuromorphic systems.Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms.Real time unsupervised learning of visual stimuli in neuromorphic VLSI systemsEmulating short-term synaptic dynamics with memristive devicesUnsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses.Spintronic Nanodevices for Bioinspired Computing.Pulse Shape and Timing Dependence on the Spike-Timing Dependent Plasticity Response of Ion-Conducting Memristors as Synapses.Event-driven contrastive divergence for spiking neuromorphic systems.Recurrent Spiking Networks Solve Planning Tasks.Three-terminal resistive switch based on metal/metal oxide redox reactions.Crossbar Nanoscale HfO2-Based Electronic Synapses.A compound memristive synapse model for statistical learning through STDP in spiking neural networksImplementation of a spike-based perceptron learning rule using TiO2-x memristors.Memristive stochastic plasticity enables mimicking of neural synchrony: Memristive circuit emulates an optical illusion.A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.Synaptic behavior and STDP of asymmetric nanoscale memristors in biohybrid systems.Reversible optical switching memristors with tunable STDP synaptic plasticity: a route to hierarchical control in artificial intelligent systems.Impact of Synaptic Device Variations on Pattern Recognition Accuracy in a Hardware Neural Network.Circuit Techniques for Online Learning of Memristive Synapses in CMOS-Memristor Neuromorphic SystemsMemristive-Based Neuromorphic Applications and Associative MemoriesNeuromorphic computing using non-volatile memory
P2860
Q27301316-75B36C3D-8106-4936-91EB-43C53758FC3FQ30826215-FD0E5C4E-4EF9-4E77-8D75-469165450F5CQ33585452-1D511A0A-3372-4EFA-BDAB-FCD50B201C63Q35833704-D63A81DC-5848-49F0-B122-4927D3518B82Q36158706-C7A0662E-FEDC-45E1-BE3B-53BB16B54637Q36423220-AB291E33-DFC4-4099-B0A0-D4D70AA3E110Q37323980-0A61551D-85B9-4131-BFA8-49440BC17D80Q37426244-9CC19EE6-856D-4EBA-A101-96302F84679CQ37531671-538CA409-D9C0-49E3-9587-7429A6A207A1Q37579640-2342FC94-5CAD-4389-B657-A198F5F6A3C6Q38542712-166FA8B4-AF37-4CD8-ADA6-54A51D64E1FDQ38636064-4E15B8E2-B3BC-43F6-A6DA-33E848765EE3Q39020025-6B13FC7E-156C-4D5C-83B0-39EE4A902692Q39063243-80442041-D16E-47E7-A4CD-70D32AB7968BQ41471261-DCA17B83-EFFE-442F-A961-EBF5D0A63314Q42631289-C364B071-37E9-47F9-9C16-BBB8BCD82664Q43107292-7D88CA3B-7509-4FE2-93E8-D05FCAA3C75EQ46129929-007C732E-82BB-40D1-A089-8F0D3854E4FCQ47310514-27208103-9676-489E-BB0E-4B02D28D1182Q49357043-D75A6358-001D-4538-B404-FBE83160DF21Q56931498-4D5D517A-BB8E-4376-A1B0-52F6DFD62C82Q58218812-33D5B119-EC2D-4D98-9378-78A0FCF09FC1Q58273367-FFA19AB6-EE5D-4349-97B0-ACFA6C45D7A1
P2860
STDP and STDP variations with memristors for spiking neuromorphic learning systems.
description
article científic
@ca
article scientifique
@fr
articol științific
@ro
articolo scientifico
@it
artigo científico
@gl
artigo científico
@pt
artigo científico
@pt-br
artikel ilmiah
@id
artikull shkencor
@sq
artículo científico
@es
name
STDP and STDP variations with memristors for spiking neuromorphic learning systems.
@en
type
label
STDP and STDP variations with memristors for spiking neuromorphic learning systems.
@en
prefLabel
STDP and STDP variations with memristors for spiking neuromorphic learning systems.
@en
P2860
P50
P356
P1476
STDP and STDP variations with memristors for spiking neuromorphic learning systems
@en
P2093
G Indiveri
P2860
P356
10.3389/FNINS.2013.00002
P577
2013-02-18T00:00:00Z