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Liam McDaid
L. J. McDaid
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- affiliation: Ulster University, UK
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2020 – today
- 2024
- [j53]Alireza Poshtkohi, John J. Wade
, Liam McDaid, Junxiu Liu, Mark Dallas
Mathematical Modeling of PI3K/Akt Pathway in Microglia. Neural Comput. 36(4): 645-676 (2024) - [i1]Andrew Walter, Shimeng Wu, Andy M. Tyrrell, Liam McDaid, Malachy McElholm, Nidhin Thandassery Sumithran, Jim Harkin, Martin A. Trefzer:
Artificial Neural Microcircuits as Building Blocks: Concept and Challenges. CoRR abs/2403.16327 (2024) - 2023
- [c55]Natasha Hamilton, Jim Harkin, Liam McDaid, Junxiu Liu, Eoghan Furey:
Feature Extraction Methods for Neural Networks in the Classification of Structural Health Anomalies. IJCCI 2023: 514-523 - 2021
- [j52]Yongchuang Huang, Junxiu Liu, Jim Harkin, Liam McDaid, Yuling Luo:
An memristor-based synapse implementation using BCM learning rule. Neurocomputing 423: 336-342 (2021) - [j51]Aqib Javed, Jim Harkin
Predicting Networks-on-Chip traffic congestion with Spiking Neural Networks. J. Parallel Distributed Comput. 154: 82-93 (2021) - [j50]Alireza Poshtkohi, John J. Wade
Mathematical modelling of human P2X-mediated plasma membrane electrophysiology and calcium dynamics in microglia. PLoS Comput. Biol. 17(11) (2021) - [c54]Aqib Javed, Jim Harkin
Spiking Neural Network-based Structural Health Monitoring Hardware System. SSCI 2021: 1-7 - 2020
- [j49]Lili Pang, Junxiu Liu
Case Study - Spiking Neural Network Hardware System for Structural Health Monitoring. Sensors 20(18): 5126 (2020) - [c53]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 - [c52]Marinus Toman
Computational Study of Astroglial Calcium Homeostasis in a Semi-isolated Synaptic Cleft. IJCNN 2020: 1-8 - [c51]Aqib Javed, Jim Harkin, Liam McDaid, Junxiu Liu:
Exploring Spiking Neural Networks for Prediction of Traffic Congestion in Networks-on-Chip. ISCAS 2020: 1-5
2010 – 2019
- 2019
- [j48]Junxiu Liu
Bio-inspired fault detection circuits based on synapse and spiking neuron models. Neurocomputing 331: 473-482 (2019) - [j47]Junxiu Liu
Exploring Self-Repair in a Coupled Spiking Astrocyte Neural Network. IEEE Trans. Neural Networks Learn. Syst. 30(3): 865-875 (2019) - [c50]Junxiu Liu, Liam McDaid, Jim Harkin
Autonomous Learning Paradigm for Spiking Neural Networks. ICANN (1) 2019: 737-744 - 2018
- [j46]Alan G. Millard
ARDebug: An Augmented Reality Tool for Analysing and Debugging Swarm Robotic Systems. Frontiers Robotics AI 5: 87 (2018) - [j45]George Martin, Jim Harkin, L. J. McDaid, John J. Wade
On-chip communication for neuro-glia networks. IET Comput. Digit. Tech. 12(4): 130-138 (2018) - [j44]Thomas Dowrick, Liam McDaid, Stephen Hall:
Fan-in analysis of a leaky integrator circuit using charge transfer synapses. Neurocomputing 314: 78-85 (2018) - [j43]Bronac Flanagan
A computational study of astrocytic glutamate influence on post-synaptic neuronal excitability. PLoS Comput. Biol. 14(4) (2018) - [j42]Kevin Breslin, John Joseph Wade
Potassium and sodium microdomains in thin astroglial processes: A computational model study. PLoS Comput. Biol. 14(5) (2018) - [j41]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) - [j40]Junxiu Liu
SPANNER: A Self-Repairing Spiking Neural Network Hardware Architecture. IEEE Trans. Neural Networks Learn. Syst. 29(4): 1287-1300 (2018) - [c49]Yuling Luo, Qian Lu, Junxiu Liu, Qiang Fu, Jim Harkin, Liam McDaid, Jordi Martínez-Corral, Guillermo Biot-Marí:
Forest fire detection using spiking neural networks. CF 2018: 371-375 - [c48]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 - [c47]Anju P. Johnson
Time-multiplexed System-on-Chip using Fault-tolerant Astrocyte-Neuron Networks. SSCI 2018: 1076-1083 - [c46]Malachy McElholm, Jim Harkin, Junxiu Liu, Liam McDaid:
Scalable Bio-inspired Fault Detection, Isolation and Recovery in NoCs. SSCI 2018: 1092-1097 - [c45]Kyle Madden
Adding Security to Networks-on-Chip using Neural Networks. SSCI 2018: 1299-1306 - [c44]Anju P. Johnson
Fault-Tolerant Learning in Spiking Astrocyte-Neural Networks on FPGAs. VLSID 2018: 49-54 - 2017
- [j39]Lei Wan, Junxiu Liu, Jim Harkin
Layered tile architecture for efficient hardware spiking neural networks. Microprocess. Microsystems 53: 21-32 (2017) - [j38]Sandeep Pande, Fearghal Morgan, Finn Krewer
Rapid application prototyping for hardware modular spiking neural network architectures. Neural Comput. Appl. 28(9): 2767-2779 (2017) - [c43]Anju P. Johnson
Homeostatic fault tolerance in spiking neural networks utilizing dynamic partial reconfiguration of FPGAs. FPT 2017: 195-198 - [c42]Junxiu Liu, Liam McDaid, Jim Harkin
Self-repairing Learning Rule for Spiking Astrocyte-Neuron Networks. ICONIP (6) 2017: 384-392 - [c41]Alan G. Millard
The Pi-puck extension board: A raspberry Pi interface for the e-puck robot platform. IROS 2017: 741-748 - [c40]Shvan Karim, Jim Harkin
Assessing Self-Repair on FPGAs with Biologically Realistic Astrocyte-Neuron Networks. ISVLSI 2017: 421-426 - [c39]Yuling Luo, Qiang Fu
An Extended Algorithm Using Adaptation of Momentum and Learning Rate for Spiking Neurons Emitting Multiple Spikes. IWANN (1) 2017: 569-579 - 2016
- [j37]Junxiu Liu, Jim Harkin
Scalable Networks-on-Chip Interconnected Architecture for Astrocyte-Neuron Networks. IEEE Trans. Circuits Syst. I Regul. Pap. 63-I(12): 2290-2303 (2016) - [c38]Junxiu Liu, Jim Harkin
Hierarchical Networks-on-Chip Interconnect for Astrocyte-Neuron Network Hardware. ICANN (1) 2016: 382-390 - [c37]Junxiu Liu, Jim Harkin
Self-repairing mobile robotic car using astrocyte-neuron networks. IJCNN 2016: 1379-1386 - [c36]Junxiu Liu, Jim Harkin
Self-repairing hardware with astrocyte-neuron networks. ISCAS 2016: 1350-1353 - [c35]Anju P. Johnson
An FPGA-based hardware-efficient fault-tolerant astrocyte-neuron network. SSCI 2016: 1-8 - [c34]George Martin, Jim Harkin
Astrocyte to spiking neuron communication using Networks-on-Chip ring topology. SSCI 2016: 1-8 - 2015
- [j36]Lvchen Cao, Yuling Luo
An authentication strategy based on spatiotemporal chaos for software copyright protection. Secur. Commun. Networks 8(18): 4073-4086 (2015) - [j35]Muhammad Naeem, Liam McDaid, Jim Harkin
On the Role of Astroglial Syncytia in Self-Repairing Spiking Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 26(10): 2370-2380 (2015) - [c33]Junxiu Liu, Jim Harkin
Case study: Bio-inspired self-adaptive strategy for spike-based PID controller. ISCAS 2015: 2700-2703 - [p1]Snaider Carrillo, Jim Harkin
Hierarchical Networks-on-Chip Architecture for Neuromorphic Hardware. Evolvable Hardware 2015: 297-330 - 2014
- [j34]Andy W. Smith, L. J. McDaid, Steve Hall:
A compact spike-timing-dependent-plasticity circuit for floating gate weight implementation. Neurocomputing 124: 210-217 (2014) - 2013
- [j33]John J. Wade
Biophysically based computational models of astrocyte ~ neuron coupling and their functional significance. Frontiers Comput. Neurosci. 7: 44 (2013) - [j32]Thomas Dowrick, Steve Hall, Liam McDaid:
A simple programmable axonal delay scheme for spiking neural networks. Neurocomputing 108: 79-83 (2013) - [j31]Sandeep Pande, Fearghal Morgan, Seamus Cawley, Tom M. Bruintjes, Gerard J. M. Smit, Brian McGinley
Modular Neural Tile Architecture for Compact Embedded Hardware Spiking Neural Network. Neural Process. Lett. 38(2): 131-153 (2013) - [j30]Sandeep Pande, Fearghal Morgan, Gerard J. M. Smit, Tom M. Bruintjes, Jochem H. Rutgers, Brian McGinley
Fixed latency on-chip interconnect for hardware spiking neural network architectures. Parallel Comput. 39(9): 357-371 (2013) - [j29]Eric Nichols, Liam McDaid, Nazmul H. Siddique:
Biologically Inspired SNN for Robot Control. IEEE Trans. Cybern. 43(1): 115-128 (2013) - [j28]Snaider Carrillo
Scalable Hierarchical Network-on-Chip Architecture for Spiking Neural Network Hardware Implementations. IEEE Trans. Parallel Distributed Syst. 24(12): 2451-2461 (2013) - 2012
- [j27]John J. Wade
Self-repair in a Bidirectionally Coupled Astrocyte-Neuron (AN) System based on Retrograde Signaling. Frontiers Comput. Neurosci. 6: 76 (2012) - [j26]Neil McDonnell, Snaider Carrillo, Jim Harkin, Liam McDaid:
Investigating Power Reduction for NoC-Based Spiking Neural Network Platforms using Channel Encoding. Int. J. Adapt. Resilient Auton. Syst. 3(4): 1-16 (2012) - [j25]Mia Nazmul Haque Siddique, Bernard Widrow, Filip Ponulak, L. J. McDaid:
Introduction. Int. J. Neural Syst. 22(4) (2012) - [j24]Arfan Ghani
Evaluating the generalisation capability of a CMOS based synapse. Neurocomputing 83: 188-197 (2012) - [j23]Cornelius Glackin, Liam P. Maguire
Synchrony: A spiking-based mechanism for processing sensory stimuli. Neural Networks 32: 26-34 (2012) - [j22]Snaider Carrillo
Advancing interconnect density for spiking neural network hardware implementations using traffic-aware adaptive network-on-chip routers. Neural Networks 33: 42-57 (2012) - [j21]Julie A. Wall
Spiking Neural Network Model of Sound Localization Using the Interaural Intensity Difference. IEEE Trans. Neural Networks Learn. Syst. 23(4): 574-586 (2012) - [j20]Thomas Dowrick, Steve Hall, Liam McDaid:
Silicon-Based Dynamic Synapse With Depressing Response. IEEE Trans. Neural Networks Learn. Syst. 23(10): 1513-1525 (2012) - [c32]Snaider Carrillo
Hierarchical Network-on-Chip and Traffic Compression for Spiking Neural Network Implementations. NOCS 2012: 83-90 - 2011
- [j19]Seamus Cawley, Fearghal Morgan, Brian McGinley
Hardware spiking neural network prototyping and application. Genet. Program. Evolvable Mach. 12(3): 257-280 (2011) - [j18]Cornelius Glackin, Liam P. Maguire
Receptive field optimisation and supervision of a fuzzy spiking neural network. Neural Networks 24(3): 247-256 (2011) - [j17]Valeriu Beiu
On Two-Layer Brain-Inspired Hierarchical Topologies - A Rent's Rule Approach -. Trans. High Perform. Embed. Archit. Compil. 4: 311-333 (2011) - [c31]Snaider Carrillo
Adaptive Routing Strategies for Large Scale Spiking Neural Network Hardware Implementations. ICANN (1) 2011: 77-84 - [c30]Sandeep Pande, Fearghal Morgan, Seamus Cawley, Brian McGinley, Jim Harkin, Snaider Carrillo, Liam McDaid:
Addressing the Hardware Resource Requirements of Network-on-chip based Neural Architectures. IJCCI (NCTA) 2011: 128-137 - [c29]Cornelius Glackin, Liam P. Maguire
Lateral inhibitory networks: Synchrony, edge enhancement, and noise reduction. IJCNN 2011: 1003-1009 - [c28]Arfan Ghani
Evaluating the training dynamics of a CMOS based synapse. IJCNN 2011: 1162-1168 - [c27]John J. Wade
Exploring retrograde signaling via astrocytes as a mechanism for self repair. IJCNN 2011: 3149-3155 - 2010
- [j16]Ammar Belatreche, Liam P. Maguire, T. Martin McGinnity, Liam McDaid
Computing with Biologically Inspired Neural Oscillators: Application to Colour Image Segmentation. Adv. Artif. Intell. 2010: 405073:1-405073:21 (2010) - [j15]Brendan P. Glackin, Julie A. Wall
A Spiking Neural Network Model of the Medial Superior Olive Using Spike Timing Dependent Plasticity for Sound Localization. Frontiers Comput. Neurosci. 4: 18 (2010) - [j14]Thomas J. Strain, L. J. McDaid, T. Martin McGinnity
An STDP Training Algorithm for a Spiking Neural Network with Dynamic Threshold Neurons. Int. J. Neural Syst. 20(6): 463-480 (2010) - [j13]Eric Nichols, L. J. McDaid, Mia Nazmul Haque Siddique:
Case Study on a Self-Organizing Spiking Neural Network for Robot Navigation. Int. J. Neural Syst. 20(6): 501-508 (2010) - [j12]John J. Wade
SWAT: A Spiking Neural Network Training Algorithm for Classification Problems. IEEE Trans. Neural Networks 21(11): 1817-1830 (2010) - [c26]Snaider Carrillo
An Efficient, High-Throughput Adaptive NoC Router for Large Scale Spiking Neural Network Hardware Implementations. ICES 2010: 133-144 - [c25]Ammar Belatreche, Liam P. Maguire
Application of biologically inspired neural oscillators to colour image segmentation. IJCNN 2010: 1-8 - [c24]Cornelius Glackin, Liam P. Maguire
Feature extraction from spectro-temporal signals using dynamic synapses, recurrency, and lateral inhibition. IJCNN 2010: 1-6 - [c23]Sandeep Pande, Fearghal Morgan, Seamus Cawley, Brian McGinley
EMBRACE-SysC for analysis of NoC-based Spiking Neural Network architectures. SoC 2010: 139-145
2000 – 2009
- 2009
- [j11]Jim Harkin, Fearghal Morgan, Liam McDaid, Steve Hall, Brian McGinley, Seamus Cawley:
A Reconfigurable and Biologically Inspired Paradigm for Computation Using Network-On-Chip and Spiking Neural Networks. Int. J. Reconfigurable Comput. 2009: 908740:1-908740:13 (2009) - [c22]Valeriu Beiu
On Two-Layer Hierarchical Networks How Does the Brain Do This? NanoNet 2009: 231-241 - [c21]Peter M. Kelly, Fergal Tuffy, Valeriu Beiu
Reduced Interconnects in Neural Networks Using a Time Multiplexed Architecture Based on Quantum Devices. NanoNet 2009: 242-250 - [c20]Arfan Ghani
Neuro inspired reconfigurable architecture for hardware/software co-design. SoCC 2009: 287-290 - 2008
- [j10]Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu, Peter M. Kelly:
A Solid-State Neuron for Spiking Neural Network Implementation. Eng. Lett. 16(1): 83-89 (2008) - [c19]Jim Harkin
Reconfigurable platforms and the challenges for large-scale implementations of spiking neural networks. FPL 2008: 483-486 - [c18]Cornelius Glackin, Liam McDaid, Liam P. Maguire
Implementing Fuzzy Reasoning on a Spiking Neural Network. ICANN (2) 2008: 258-267 - [c17]Peter M. Kelly, Liam McDaid, Fergal Tuffy, T. Martin McGinnity
A time multiplexed architecture for neural networks using quantum devices. ICECS 2008: 514-517 - [c16]Yajie Chen, Liam McDaid, Steve Hall, Peter M. Kelly:
A programmable facilitating synapse device. IJCNN 2008: 1615-1620 - [c15]Julie A. Wall
Spiking neuron models of the medial and lateral superior olive for sound localisation. IJCNN 2008: 2641-2647 - [c14]John J. Wade
SWAT: An unsupervised SNN training algorithm for classification problems. IJCNN 2008: 2648-2655 - [c13]Basheer A. M. Madappuram, Valeriu Beiu
On brain-inspired connectivity and hybrid network topologies. NANOARCH 2008: 54-61 - 2007
- [j9]Fergal Tuffy, L. J. McDaid, Vunfu Wong Kwan, John Alderman, T. Martin McGinnity
Inter-neuron communication strategies for spiking neural networks. Neurocomputing 71(1-3): 30-44 (2007) - [c12]Thomas Dowrick, Steve Hall, Liam McDaid, Octavian Buiu
A Biologically Plausible Neuron Circuit. IJCNN 2007: 715-719 - [c11]Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu, Peter M. Kelly:
Analog Spiking Neuron with Charge-Coupled Synapses. World Congress on Engineering 2007: 440-444 - 2006
- [c10]Fergal Tuffy, Liam McDaid, T. Martin McGinnity, Jose Santos, Peter M. Kelly, Vunfu Wong Kwan, John Alderman:
A Time Multiplexing Architecture for Inter-neuron Communications. ICANN (1) 2006: 944-952 - [c9]Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu, Peter M. Kelly:
On the Design of a Low Power Compact Spiking Neuron Cell Based on Charge-Coupled Synapses. IJCNN 2006: 1511-1517 - [c8]Fergal Tuffy, Liam McDaid, Vunfu Wong Kwan, John Alderman, T. Martin McGinnity, Peter M. Kelly, Jose A. Santos:
Inter-Neuron Communications for Large-Scale Neural Networks using Capacitive Coupling. IJCNN 2006: 2779-2784 - [c7]Thomas J. Strain, Liam McDaid, Liam P. Maguire
A Supervised STDP Based Training Algorithm with Dynamic Threshold Neurons. IJCNN 2006: 3409-3414 - [c6]Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu, Peter M. Kelly:
A Silicon Synapse Based on a Charge Transfer Device for Spiking Neural Network Application. ISNN (2) 2006: 1366-1373 - 2005
- [c5]Michael J. Callaghan, T. Martin McGinnity
Evolving Task Specific Algorithms for Machine Vision Applications. ICITA (1) 2005: 371-374 - [c4]Peter M. Kelly, T. Martin McGinnity, Liam P. Maguire
A Quaternary CLB Design Using Quantum Device Technology on Silicon for FPGA Neural Network Architectures. IWANN 2005: 564-571 - 2004
- [j8]C. T. Carr, T. Martin McGinnity
Integration of UML and VHDL-AMS for analogue system modelling. Formal Aspects Comput. 16(1): 80-94 (2004) - [c3]C. T. Carr, T. Martin McGinnity, L. J. McDaid:
VHDL-AMS code gneration from UML structural representations. FDL 2004: 12-25 - [c2]Michael J. Callaghan, T. Martin McGinnity
Third order loose coupled hybrid intelligent system for machine vision applications. SMC (4) 2004: 3680-3685 - 2001
- [j7]B. Roche, T. Martin McGinnity, Liam P. Maguire
Signalling techniques and their effect on neural network implementation sizes. Inf. Sci. 132(1-4): 67-82 (2001)
1990 – 1999
- 1999
- [j6]B. Roche, T. Martin McGinnity
Modeling architectures for VLSI Implementations of Fuzzy Logic Systems. Inf. Sci. 115(1-4): 1-9 (1999) - [j5]Liam P. Maguire
Issues in the development of an integrated environment for embedded system design: Part A: user needs and commercial products. Microprocess. Microsystems 23(4): 191-197 (1999) - [j4]Liam P. Maguire
Issues in the development of an integrated environment for embedded system design: Part B: design and implementation. Microprocess. Microsystems 23(4): 199-206 (1999) - [c1]Liam P. Maguire, T. Martin McGinnity, L. J. McDaid:
From a Fuzzy Flip-Flop to a MVL Flip-Flop. ISMVL 1999: 294-299 - 1998
- [j3]Liam P. Maguire
Predicting a Chaotic Time Series using Fuzzy Neural network. Inf. Sci. 112(1-4): 125-136 (1998) - [j2]J. J. Blake, Liam P. Maguire
The Implementation of Fuzzy Systems, Neural Networks and Fuzzy Neural Networks using FPGAs. Inf. Sci. 112(1-4): 151-168 (1998) - 1997
- [j1]L. J. McDaid, T. Martin McGinnity
Hardware Implementation of a Membership Function Generator for Fuzzy Reasoning. Inf. Sci. 96(1&2): 93-105 (1997)
Coauthor Index
[i1] [c55] [j52] [j51] [c54] [j49] [c53] [c52] [c51] [j48] [j47] [c50] [j45] [j43] [j42] [j41] [j40] [c49] [c48] [c47] [c46] [c45] [c44] [j39] [j38] [c43] [c42] [c40] [c39] [j37] [c38] [c37] [c36] [c35] [c34] [j36] [j35] [c33] [p1] [j33] [j31] [j30] [j28] [j27] [j26] [j22] [c32] [j19] [c31] [c30] [c27] [c26] [c23] [j11] [c19]
T. Martin McGinnity
aka: Thomas Martin McGinnity
aka: Thomas Martin McGinnity
Andrew M. Tyrrell
aka: Andy M. Tyrrell
aka: Andy M. Tyrrell
John J. Wade
aka: John Joseph Wade
aka: John Joseph Wade
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