Low Cost Interconnected Architecture for the Hardware Spiking Neural Networks
- Submitting institution
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University of Ulster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 78480320
- Type
- D - Journal article
- DOI
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10.3389/fnins.2018.00857
- Title of journal
- Frontiers in Neurosciences
- Article number
- 857
- First page
- 1
- Volume
- 12
- Issue
- -
- ISSN
- 1662-4548
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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6
- Research group(s)
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A - Intelligent Systems Research Centre
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- <01>This work led a to consortium involving Ulster, Guangxi Normal University (Dr. Luo) and Guilin Earthquake Administration (Government Organization), which secured a Global Challenge Research Fund Pump priming award (£22K) to further investigate the smart analytics of sensory data using physically robust and efficient spiking neural network computing technology. A fully funded 6-month China Research Council Scholarship was subsequently awarded to research visitor Dr Lili Pang from Nanjing Institute of Technology. Dr Pang continued to work on the data analytics of earthquake activities from Sep 2019 to March 2020 which resulted a further paper 10.3390/s20185126.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -