publication . Preprint . 2015

Energy-efficient neuromorphic classifiers

Martí, Daniel; Rigotti, Mattia; Seok, Mingoo; Fusi, Stefano;
Open Access English
  • Published: 01 Jul 2015
Neuromorphic engineering combines the architectural and computational principles of systems neuroscience with semiconductor electronics, with the aim of building efficient and compact devices that mimic the synaptic and neural machinery of the brain. Neuromorphic engineering promises extremely low energy consumptions, comparable to those of the nervous system. However, until now the neuromorphic approach has been restricted to relatively simple circuits and specialized functions, rendering elusive a direct comparison of their energy consumption to that used by conventional von Neumann digital machines solving real-world tasks. Here we show that a recent technolo...
free text keywords: Quantitative Biology - Neurons and Cognition, Computer Science - Neural and Evolutionary Computing
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