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. 2014 Dec 16;8:412. doi: 10.3389/fnins.2014.00412

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Copyright © 2014 Bill and Legenstein.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Influence of the synaptic resolution. (A) Examples of learned weight matrices with different numbers of constituents M per synapse. Even binary weights with only one stochastic switch learn to maintain a coarse image of prototypic digits. In the limit of large M, compound synapses support a quasi-continuous weight spectrum. (B) Classification error for different weight resolutions after 5000 s of learning, based on 20 independently trained networks for each value of M. Errorbars: SD among networks.