On the computational power and complexity of Spiking Neural Networks-Reference-Cited by-同舟云学术

On the computational power and complexity of Spiking Neural Networks

Published:2020-03-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Neuro-inspired Computational Elements Workshop
language:
Short-container-title:

Author:

Kwisthout Johan¹,Donselaar Nils²

Affiliation:

1. Donders Institute for Brain, Cognition, and Behaviour Nijmegen and Intel Corporation

2. Donders Institute for Brain, Cognition, and Behaviour Nijmegen and NWO

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3381755.3381760

Reference15 articles.

1. Can programming be liberated from the von Neumann style?

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3. A. Graves G. Wayne and I. Danihelka. 2014. Neural Turing Machines. arXiv:1410.5401. (2014). A. Graves G. Wayne and I. Danihelka. 2014. Neural Turing Machines. arXiv:1410.5401. (2014).

4. On the computational complexity of algorithms

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