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David M. Halliday
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2020 – today
- 2020
- [j14]Timothy O. West
, David M. Halliday
Measuring directed functional connectivity using non-parametric directionality analysis: Validation and comparison with non-parametric Granger Causality. NeuroImage 218: 116796 (2020)
2010 – 2019
- 2019
- [j13]Meaghan Elizabeth Spedden
The development of functional and directed corticomuscular connectivity during tonic ankle muscle contraction across childhood and adolescence. NeuroImage 191: 350-360 (2019) - [j12]Junxiu Liu
Exploring Self-Repair in a Coupled Spiking Astrocyte Neural Network. IEEE Trans. Neural Networks Learn. Syst. 30(3): 865-875 (2019) - [c26]Junxiu Liu, Liam McDaid, Jim Harkin
Autonomous Learning Paradigm for Spiking Neural Networks. ICANN (1) 2019: 737-744 - 2018
- [j11]Alan G. Millard
ARDebug: An Augmented Reality Tool for Analysing and Debugging Swarm Robotic Systems. Frontiers Robotics AI 5: 87 (2018) - [j10]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) - [c25]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 - [c24]Anju P. Johnson
Time-multiplexed System-on-Chip using Fault-tolerant Astrocyte-Neuron Networks. SSCI 2018: 1076-1083 - [c23]Yaoru Yang, David M. Halliday
A Unified Framework of Third Order Time and Frequency Domain Analysis for Neural Spike Trains. SSP 2018: 707-711 - [c22]Anju P. Johnson
Fault-Tolerant Learning in Spiking Astrocyte-Neural Networks on FPGAs. VLSID 2018: 49-54 - 2017
- [c21]Sopapun Suwansawang, David M. Halliday:
Time-frequency based Coherence and Phase Locking Value Analysis of Human Locomotion Data using Generalized Morse Wavelets. BIOSIGNALS 2017: 34-41 - [c20]Anju P. Johnson
Homeostatic fault tolerance in spiking neural networks utilizing dynamic partial reconfiguration of FPGAs. FPT 2017: 195-198 - [c19]Junxiu Liu, Liam McDaid, Jim Harkin
Self-repairing Learning Rule for Spiking Astrocyte-Neuron Networks. ICONIP (6) 2017: 384-392 - [c18]Alan G. Millard
The Pi-puck extension board: A raspberry Pi interface for the e-puck robot platform. IROS 2017: 741-748 - [c17]Shvan Karim, Jim Harkin
Assessing Self-Repair on FPGAs with Biologically Realistic Astrocyte-Neuron Networks. ISVLSI 2017: 421-426 - 2016
- [c16]Junxiu Liu, Jim Harkin
Self-repairing mobile robotic car using astrocyte-neuron networks. IJCNN 2016: 1379-1386 - [c15]Anju P. Johnson
An FPGA-based hardware-efficient fault-tolerant astrocyte-neuron network. SSCI 2016: 1-8 - [c14]Ibrahim Ozturk
Mapping spatio-temporally encoded patterns by reward-modulated STDP in Spiking neurons. SSCI 2016: 1-8 - 2013
- [c13]J. A. Sanchez, David M. Halliday
Reducing the effect of correlated brain sources in MEG using a linearly constrained spatial filter based on Minimum Norm. ACSSC 2013: 1828-1832 - 2011
- [j9]Gul Muhammad Khan, Julian F. Miller, David M. Halliday
Evolution of Cartesian Genetic Programs for Development of Learning Neural Architecture. Evol. Comput. 19(3): 469-523 (2011)
2000 – 2009
- 2009
- [c12]Gul Muhammad Khan, Julian Francis Miller, David M. Halliday
In search of intelligent genes: The cartesian genetic programming computational neuron (CGPCN). IEEE Congress on Evolutionary Computation 2009: 574-581 - 2008
- [c11]Gul Muhammad Khan, Julian Francis Miller, David M. Halliday:
Developing neural structure of two agents that play checkers using cartesian genetic programming. GECCO (Companion) 2008: 2169-2174 - [c10]Gul Muhammad Khan, Julian Francis Miller, David M. Halliday:
Coevolution of Neuro-developmental Programs That Play Checkers. ICES 2008: 352-361 - [c9]Maizura Mokhtar
Hippocampus-Inspired Spiking Neural Network on FPGA. ICES 2008: 362-371 - [c8]Gul Muhammad Khan, Julian Francis Miller, David M. Halliday
Breaking the Synaptic Dogma: Evolving a Neuro-inspired Developmental Network. SEAL 2008: 11-20 - 2007
- [j8]M. Griffin, David M. Halliday
Temporal sub units in dendritic trees. Biosyst. 87(2-3): 172-178 (2007) - [j7]Stephen L. Smith
Diagnosis of Parkinson's disease using evolutionary algorithms. Genet. Program. Evolvable Mach. 8(4): 433-447 (2007) - [j6]John-Stuart Brittain
Single-Trial Multiwavelet Coherence in Application to Neurophysiological Time Series. IEEE Trans. Biomed. Eng. 54(5): 854-862 (2007) - [j5]Will Barker, David M. Halliday
Fault Tolerance Using Dynamic Reconfiguration on the POEtic Tissue. IEEE Trans. Evol. Comput. 11(5): 666-684 (2007) - [c7]Gul Muhammad Khan, Julian Francis Miller, David M. Halliday
Coevolution of intelligent agents using cartesian genetic programming. GECCO 2007: 269-276 - [c6]Gul Muhammad Khan, Julian F. Miller, David M. Halliday
A developmental model of neural computation using cartesian genetic programming. GECCO (Companion) 2007: 2535-2542 - [c5]Maizura Mokhtar
Hippocampus Neurons and Place Cells/Place Field Representation to Provide Path Navigation. IJCNN 2007: 795-800 - [c4]Maizura Mokhtar
Autonomous Navigational Controller Inspired by the Hippocampus. IJCNN 2007: 813-818 - 2006
- [j4]David M. Halliday
Neural spike train synchronization indices: definitions, interpretations, and applications. IEEE Trans. Biomed. Eng. 53(6): 1056-1066 (2006) - [c3]David Allen, David M. Halliday, Andy M. Tyrrell:
A Hybrid Bio-inspired System: Hardware Spiking Neural Network Incorporating Hebbian Learning with Microprocessor Based Evolutionary Control Algorithm. IEEE Congress on Evolutionary Computation 2006: 2958-2965 - 2004
- [j3]M. Griffin, David M. Halliday
Axial current reversal promotes synchronous correlation between dendritic membrane potentials during large-scale synaptic input. Neurocomputing 58-60: 423-430 (2004) - 2003
- [c2]Jan Eriksson, Oriol Torres, Andrew Mitchell, Gayle Tucker, Ken Lindsay, David M. Halliday, Jay R. Rosenberg, Juan Manuel Moreno, Alessandro E. P. Villa
Spiking Neural Networks for Reconfigurable POEtic Tissue. ICES 2003: 165-173 - 2001
- [c1]David M. Halliday:
Temporal Coding in Neuronal Populations in the Presence of Axonal and Dendritic Conduction Time Delays. Emergent Neural Computational Architectures Based on Neuroscience 2001: 285-295 - 2000
- [j2]David M. Halliday
Weak, Stochastic Temporal Correlation of Large-Scale Synaptic Input Is a Major Determinant of Neuronal Bandwidth. Neural Comput. 12(3): 693-707 (2000)
1990 – 1999
- 1998
- [j1]David M. Halliday
Generation and characterization of correlated spike trains. Comput. Biol. Medicine 28(2): 143-152 (1998)
1980 – 1989
- 1986
- [b1]David M. Halliday:
Application of point-process system identification techniques to complex physiological systems. University of Glasgow, UK, 1986
Coauthor Index
aka: Andy M. Tyrrell
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