Noisy Spiking Neurons with Temporal Coding Have More Computational Power than Sigmoidal Neurons
Abstract
We exhibit a novel way of simulating sigmoidal neural nets by net(cid:173) works of noisy spiking neurons in temporal coding. Furthermore it is shown that networks of noisy spiking neurons with temporal coding have a strictly larger computational power than sigmoidal neural nets with the same number of units.
Cite
Text
Maass. "Noisy Spiking Neurons with Temporal Coding Have More Computational Power than Sigmoidal Neurons." Neural Information Processing Systems, 1996.Markdown
[Maass. "Noisy Spiking Neurons with Temporal Coding Have More Computational Power than Sigmoidal Neurons." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/maass1996neurips-noisy/)BibTeX
@inproceedings{maass1996neurips-noisy,
title = {{Noisy Spiking Neurons with Temporal Coding Have More Computational Power than Sigmoidal Neurons}},
author = {Maass, Wolfgang},
booktitle = {Neural Information Processing Systems},
year = {1996},
pages = {211-217},
url = {https://mlanthology.org/neurips/1996/maass1996neurips-noisy/}
}