An FPGA-based Hardware-Efficient Fault-Tolerant Astrocyte-Neuron Network

Anju P. Johnson; David M. Halliday; Alan G. Millard; Andy M. Tyrrell; Jon Timmis; Junxiu Liu; Jim Harkin; Liam McDaid; Shvan Karim

An FPGA-based Hardware-Efficient Fault-Tolerant Astrocyte-Neuron Network

Anju P. Johnson, David M. Halliday, Alan G. Millard, Andy M. Tyrrell, Jon Timmis, Junxiu Liu, Jim Harkin, Liam McDaid, Shvan Karim

Electronic Engineering

Research output: Contribution to conference › Paper › peer-review

Original language	English
Publication status	Accepted/In press - 2016
Event	The 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016) - Athens, Greece, United Kingdom Duration: 6 Dec 2016 → 9 Dec 2016

Conference

Conference	The 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016)
Country/Territory	United Kingdom
City	Greece
Period	6/12/16 → 9/12/16

Self-repairing hardware paradigms based on astrocyte-neuron models
Halliday, D. M., Timmis, J. & Tyrrell, A.
EPSRC
1/10/15 → 31/10/19
Project: Research project (funded) › Research

Cite this

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title = "An FPGA-based Hardware-Efficient Fault-Tolerant Astrocyte-Neuron Network",

author = "Johnson, {Anju P.} and Halliday, {David M.} and Millard, {Alan G.} and Tyrrell, {Andy M.} and Jon Timmis and Junxiu Liu and Jim Harkin and Liam McDaid and Shvan Karim",

year = "2016",

language = "English",

note = "The 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016) ; Conference date: 06-12-2016 Through 09-12-2016",

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TY - CONF

T1 - An FPGA-based Hardware-Efficient Fault-Tolerant Astrocyte-Neuron Network

AU - Johnson, Anju P.

AU - Halliday, David M.

AU - Millard, Alan G.

AU - Tyrrell, Andy M.

AU - Timmis, Jon

AU - Liu, Junxiu

AU - Harkin, Jim

AU - McDaid, Liam

AU - Karim, Shvan

PY - 2016

Y1 - 2016

M3 - Paper

T2 - The 2016 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2016)

Y2 - 6 December 2016 through 9 December 2016

ER -

An FPGA-based Hardware-Efficient Fault-Tolerant Astrocyte-Neuron Network

Conference

Projects

Self-repairing hardware paradigms based on astrocyte-neuron models

Cite this