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Spatiotemporal neural networks for link-state routing protocols

Authors: J. Meador; Nasir Shaikh-Husin;

Spatiotemporal neural networks for link-state routing protocols

Abstract

This paper discusses the application of a mixed-signal VLSI realization of a recurrent spatiotemporal neural network to a computer network routing. The neural network exhibits a regular interconnect structure and uses simple processing units in a combination which is well suited for VLSI implementation with a standard fabrication process. Its ability to rapidly arrive at solutions to the single-source multiple-destination routing problem makes it particularly attractive for link-state network routing protocols.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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