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Rueckauer et al., 2018 - Google Patents

Conversion of analog to spiking neural networks using sparse temporal coding

Rueckauer et al., 2018

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Document ID
14004824790640693140
Author
Rueckauer B
Liu S
Publication year
Publication venue
2018 IEEE international symposium on circuits and systems (ISCAS)

External Links

Snippet

The activations of an analog neural network (ANN) are usually treated as representing an analog firing rate. When mapping the ANN onto an equivalent spiking neural network (SNN), this rate-based conversion can lead to undesired increases in computation cost and memory …
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Classifications

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    • G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
    • G06N3/0635—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
    • G—PHYSICS
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