Liam Maguire
Liam Maguire
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TitleCited byYear
Predicting a chaotic time series using a fuzzy neural network
LP Maguire, B Roche, TM McGinnity, LJ McDaid
Information Sciences 112 (1-4), 125-136, 1998
Fault diagnosis of electronic systems using intelligent techniques: A review
WG Fenton, TM McGinnity, LP Maguire
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2001
Challenges for large-scale implementations of spiking neural networks on FPGAs
LP Maguire, TM McGinnity, B Glackin, A Ghani, A Belatreche, J Harkin
Neurocomputing 71 (1-3), 13-29, 2007
Statistical and computational intelligence techniques for inferential model development: a comparative evaluation and a novel proposition for fusion
K Warne, G Prasad, S Rezvani, L Maguire
Engineering applications of artificial intelligence 17 (8), 871-885, 2004
Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process
P Humphreys, A McCloskey, R McIvor, L Maguire, C Glackin
International Journal of Production Research 44 (12), 2379-2419, 2006
Advances in design and application of spiking neural networks
A Belatreche, LP Maguire, M McGinnity
Soft Computing 11 (3), 239-248, 2007
Minimizing the bullwhip effect in a supply chain using genetic algorithms
T O’donnell, L Maguire, R McIvor, P Humphreys
International Journal of Production Research 44 (8), 1523-1543, 2006
Selecting critical patterns based on local geometrical and statistical information
Y Li, L Maguire
IEEE transactions on pattern analysis and machine intelligence 33 (6), 1189-1201, 2010
A novel approach for the implementation of large scale spiking neural networks on FPGA hardware
B Glackin, TM McGinnity, LP Maguire, QX Wu, A Belatreche
International Work-Conference on Artificial Neural Networks, 552-563, 2005
An experimental evaluation of novelty detection methods
X Ding, Y Li, A Belatreche, LP Maguire
Neurocomputing 135, 313-327, 2014
A thalamo–cortico–thalamic neural mass model to study alpha rhythms in Alzheimer’s disease
BS Bhattacharya, D Coyle, LP Maguire
Neural networks 24 (6), 631-645, 2011
Client–server architecture for collaborative remote experimentation
MJ Callaghan, J Harkin, E McColgan, TM McGinnity, LP Maguire
Journal of Network and Computer Applications 30 (4), 1295-1308, 2007
The implementation of fuzzy systems, neural networks and fuzzy neural networks using FPGAs
JJ Blake, LP Maguire, TM McGinnity, B Roche, LJ McDaid
Information sciences 112 (1-4), 151-168, 1998
Edge detection based on spiking neural network model
QX Wu, M McGinnity, L Maguire, A Belatreche, B Glackin
International Conference on Intelligent Computing, 26-34, 2007
An online supervised learning method for spiking neural networks with adaptive structure
J Wang, A Belatreche, L Maguire, TM Mcginnity
Neurocomputing 144, 526-536, 2014
Using a fuzzy approach to support financial analysis in the corporate acquisition process
RT McIvor, AG McCloskey, PK Humphreys, LP Maguire
Expert Systems with Applications 27 (4), 533-547, 2004
Partitioning methodology for dynamically reconfigurable embedded systems
J Harkin, TM McGinnity, LP Maguire
IEE Proceedings-Computers and Digital Techniques 147 (6), 391-396, 2000
Learning under weight constraints in networks of temporal encoding spiking neurons
QX Wu, TM McGinnity, LP Maguire, B Glackin, A Belatreche
Neurocomputing 69 (16-18), 1912-1922, 2006
Intelligent user support in autonomous remote experimentation environments
MJ Callaghan, J Harkin, TM McGinnity, LP Maguire
IEEE Transactions on Industrial Electronics 55 (6), 2355-2367, 2008
A method for supervised training of spiking neural networks
A Belatreche, LP Maguire, M McGinnity, QX Wu
Cybernetic Intelligence, Challenges and Advances, 11, 2003
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