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Shvan Karim
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2020 – today
- 2021
- [j3]Daniel Kelly, Karla Muñoz Esquivel
, James Gillespie
Feasibility of Sensor Technology for Balance Assessment in Home Rehabilitation Settings. Sensors 21(13): 4438 (2021) - 2020
- [c9]Shvan Karim, Jim Harkin, Liam McDaid, Bryan Gardiner, Junxiu Liu:
AstroByte: Multi-FPGA Architecture for Accelerated Simulations of Spiking Astrocyte Neural Networks. DATE 2020: 1568-1573
2010 – 2019
- 2019
- [j2]Junxiu Liu
Exploring Self-Repair in a Coupled Spiking Astrocyte Neural Network. IEEE Trans. Neural Networks Learn. Syst. 30(3): 865-875 (2019) - [c8]Junxiu Liu, Liam McDaid, Jim Harkin
Autonomous Learning Paradigm for Spiking Neural Networks. ICANN (1) 2019: 737-744 - 2018
- [j1]Anju P. Johnson
Homeostatic Fault Tolerance in Spiking Neural Networks: A Dynamic Hardware Perspective. IEEE Trans. Circuits Syst. I Regul. Pap. 65-I(2): 687-699 (2018) - [c7]Shvan Karim, Jim Harkin, Liam McDaid, Bryan Gardiner
FPGA-based Fault-injection and Data Acquisition of Self-repairing Spiking Neural Network Hardware. ISCAS 2018: 1-5 - [c6]Anju P. Johnson
Time-multiplexed System-on-Chip using Fault-tolerant Astrocyte-Neuron Networks. SSCI 2018: 1076-1083 - [c5]Anju P. Johnson
Fault-Tolerant Learning in Spiking Astrocyte-Neural Networks on FPGAs. VLSID 2018: 49-54 - 2017
- [c4]Anju P. Johnson
Homeostatic fault tolerance in spiking neural networks utilizing dynamic partial reconfiguration of FPGAs. FPT 2017: 195-198 - [c3]Junxiu Liu, Liam McDaid, Jim Harkin
Self-repairing Learning Rule for Spiking Astrocyte-Neuron Networks. ICONIP (6) 2017: 384-392 - [c2]Shvan Karim, Jim Harkin
Assessing Self-Repair on FPGAs with Biologically Realistic Astrocyte-Neuron Networks. ISVLSI 2017: 421-426 - 2016
- [c1]Anju P. Johnson
An FPGA-based hardware-efficient fault-tolerant astrocyte-neuron network. SSCI 2016: 1-8
Coauthor Index
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