2008 · 31 citations · 12 references
Life SciencesComputer EngineeringComputer SystemsNeural EngineeringReconfigurable ComputingSynaptic PlasticityActivity-dependent PlasticityHebbian PlasticityMemristive MaterialsNeural CircuitsSpiking Neural NetworksSynaptic TransmissionInitial State EffectsIntegrate-and-fire Neuron ModelsNeuromorphic DevicesNeuromorphic HardwarePlastic Neural NetworksRecurrent Spiking Neural NetworksSpike-frequency AdaptationVlsi Implementation
We describe and demonstrate a neuromorphic, analog VLSI chip (termed F-LANN) hosting 128 integrate-and-fire (IF) neurons with spike-frequency adaptation, and 16,384 plastic bistable synapses implementing a self-regulated form of Hebbian, spike-driven, stochastic plasticity. The chip is designed to offer a high degree of reconfigurability: each synapse may be individually configured at any time to be either excitatory or inhibitory and to receive either recurrent input from an on-chip neuron or AER-based input from an off-chip neuron. The initial state of each synapse can be set as potentiated or depressed, and the state of each synapse can be read and stored on a computer.
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Jiří Beneš · Kybernetika · 1990 · 650 citations
Synaptic Dynamics in Analog VLSI
Chiara Bartolozzi, Giacomo Indiveri · Neural Computation · 2007 · 381 citations · Full text
Learning in Neural Networks with Material Synapses
Daniel J. Amit, Stefano Fusi · Neural Computation · 1994 · 313 citations · Full text
Life Sciences, Neuroscience, Memory +16