CrossNets: Neuromorphic networks for nanoelectronic implementation Hybrid “CMOL” integrated circuits, incorporating advanced CMOS devices for neural cell bodies, nanowires as axons and dendrites, and single-molecule latching switches as synapses, may be used for the hardware implementation of extremely dense (∼10 7 cells and ∼10 12 synapses per cm 2 ) neuromorphic networks, operating up to 10 6 times faster than their biological prototypes. We are exploring several “CrossNet” architectures that accommodate the limitations imposed by CMOL hardware and should allow effective training of the networks without a direct external access to individual synapses. CrossNet training in the Hopfield mode have been confirmed on a software model of the network.
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References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Afifi, Ahmad; Ayatollahi, Ahmad; Raissi, Farshid: CMOL implementation of spiking neurons and spike-timing dependent plasticity (2011)
- Türel, Özgür; Likharev, Konstantin: CrossNets: Possible neuromorphic networks based on nanoscale components (2003)
- Türel, Özgür; Likharev, Konstantin: CrossNets: Neuromorphic networks for nanoelectronic implementation (2003)