Definition
Like biological networks, hardware neuromorphic networks are built up of neurons and synapses. The emergence of memristors, innovative electronic components with plasticity properties similar to those of synapses, offers a new technological solution for building neuromorphic VLSI.
Detailed Description
The design of analog silicon neurons has now been mastered (Indiveri et al. 2011), lowering computational cost down to a picojoule per action potential. However, considering a ratio of 1,000 synapses to 1 neuron, as observed in biological networks, the bottleneck in designing large- to very large-scale networks is likely to be integrating synapses and related connectivity. Artificial synapses with synaptic plasticity require three computational elements: generation of synaptic current, storage of synaptic weight, and plasticity calculation. Memristors present the advantage of combining these three elements in a single...
References
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Indiveri G, Linares-Barranco B, Hamilton TJ, van Schaik A, Etienne-Cummings R, Delbruck T, Liu S-C, Dudek P, Häfliger P, Renaud S, Schemmel J, Cauwenberghs G, Arthur J, Hynna K, Folowosele F, Saïghi S, Serrano-Gotarredona T, Wijekoon J, Wang Y, Boahen K (2011) Neuromorphic silicon neuron circuits. Front Neurosci 5:73
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Further Reading
Chang T, Yang Y, Lu W (2013) Building neuromorphic circuits with memristive devices. IEEE Circuits Syst Mag 13(2):56–73
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Saïghi, S. (2014). Neuromorphic Technologies, Memristors. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_116-1
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DOI: https://doi.org/10.1007/978-1-4614-7320-6_116-1
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