The Library
Browse by Warwick Author
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Jump to: ARC Communications Research Network | Australian Research Council | Australian Research Council (ARC) | Australian Research Council Post Doctoral Fellowship | DNV GL (Firm) | Deutscher Akademischer Austauschdienst (DAAD) | Economic and Social Research Council (Great Britain) (ESRC) | Engineering and Physical Sciences Research Council (EPSRC) | European Commission (EC) | Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation (China)] (NSFC) | Innovate UK | Medical Research Council (Great Britain) (MRC) | UK Overseas Research Students Awards Scheme (ORSAS) | United States. Office of Naval Research | University of Sussex | Warwick Institute of Advanced Study (IAS) | Warwick Postgraduate Research Fellowship (WPRF)
Number of items: 29.
ARC Communications Research Network
Stocks, Nigel G., McDonnell, Mark D., Morse, Robert P. and Nikitin, Alexander (2009) The role of stochasticity in an information-optimal neural population code. In: International Workshop on Statistical-Mechanical Informatics, Kyoto, Japan, September 13, 2009. Published in: Journal of Physics: Conference Series, Vol.197 Article no. 012015. doi:10.1088/1742-6596/197/1/012015 ISSN 1742-6588.
Australian Research Council
McDonnell, Mark D., Amblard, Pierre-Olivier and Stocks, Nigel G. (2010) Bio-inspired communication: performance limits for information transmission and compression in stochastic pooling networks with binary quantizing nodes. Journal of Computational and Theoretical Nanoscience, Vol.7 (No.5). pp. 876-883. doi:10.1166/jctn.2010.1434 ISSN 1546-1955.
Nikitin, Alexander P., Stocks, Nigel G., Morse, Robert P. and McDonnell, Mark D. (2009) Neural population coding is optimized by discrete tuning curves. Physical Review Letters, Vol.103 (No.13). Article: 138101. doi:10.1103/PhysRevLett.103.138101 ISSN 0031-9007.
Stocks, Nigel G., McDonnell, Mark D., Morse, Robert P. and Nikitin, Alexander (2009) The role of stochasticity in an information-optimal neural population code. In: International Workshop on Statistical-Mechanical Informatics, Kyoto, Japan, September 13, 2009. Published in: Journal of Physics: Conference Series, Vol.197 Article no. 012015. doi:10.1088/1742-6596/197/1/012015 ISSN 1742-6588.
Australian Research Council (ARC)
McDonnell, Mark D. and Stocks, Nigel G. (2008) Maximally informative stimuli and tuning curves for sigmoidal rate-coding neurons and populations. Physical Review Letters, Vol.101 (No.5). doi:10.1103/PhysRevLett.101.058103 ISSN 0031-9007.
McDonnell, Mark D. and Stocks, Nigel G. (2008) Optimal sigmoidal tuning curves for intensity encoding sensory neurons with quasi-Poisson variability. In: Seventeenth Annual Computational Neuroscience Meeting: CNS*2008, Portland, USA, 19-24 Jul 2008. Published in: BMC Neuroscience, Vol.9 (Suppl.1). p. 117. doi:10.1186/1471-2202-9-S1-P117 ISSN 1471-2202.
Australian Research Council Post Doctoral Fellowship
McDonnell, Mark D., Amblard, Pierre-Olivier and Stocks, Nigel G. (2009) Stochastic pooling networks. Journal of Statistical Mechanics: Theory and Experiment, Vol.2009 (January 2009). Article: P01012. doi:10.1088/1742-5468/2009/01/P01012 ISSN 1742-5468.
DNV GL (Firm)
Ahmed, A., Bengherbia, T., Zhvansky, R., Ferrara, G., Wen, J. X. (Jennifer X.) and Stocks, Nigel G. (2016) Validation of geometry modelling approaches for offshore gas dispersion simulations. Journal of Loss Prevention in the Process Industries, 44 . pp. 594-600. doi:10.1016/j.jlp.2016.07.009 ISSN 0950-4230.
Deutscher Akademischer Austauschdienst (DAAD)
Freund, Jan A., Nikitin, Alexander and Stocks, Nigel G. (2010) Phase locking below rate threshold in noisy model neurons. Neural Computation, Vol.22 (No.3). pp. 599-620. doi:10.1162/neco.2009.01-09-934 ISSN 0899-7667.
Economic and Social Research Council (Great Britain) (ESRC)
Yang, Jianhua, Singh, Harsimrat, Hines, Evor, Schlaghecken, Friederike, Iliescu, Daciana, Leeson, Mark S. and Stocks, Nigel G. (2012) Channel selection and classification of electroencephalogram signals: an artificial neural network and genetic algorithm-based approach. Artificial Intelligence In Medicine, Volume 55 (Number 2). pp. 117-126. doi:10.1016/j.artmed.2012.02.001 ISSN 1873-2860.
Engineering and Physical Sciences Research Council (EPSRC)
Daneshkhah, Alireza, Stocks, Nigel G. and Jeffrey, Paul (2017) Probabilistic sensitivity analysis of optimised preventive maintenance strategies for deteriorating infrastructure assets. Reliability Engineering & System Safety, 163 . pp. 33-45. doi:10.1016/j.ress.2017.02.002 ISSN 0951-8320.
Morse, Robert P., Allingham, D. and Stocks, Nigel G. (2015) Stimulus-dependent refractoriness in the Frankenhaeuser-Huxley model. Journal of Theoretical Biology, 382 . pp. 397-404. doi:10.1016/j.jtbi.2015.07.002 ISSN 0022-5193.
Morse, Robert P., Allingham, D. and Stocks, Nigel G. (2015) A phenomenological model of myelinated nerve with a dynamic threshold. Journal of Theoretical Biology, 382 . pp. 386-396. doi:10.1016/j.jtbi.2015.06.035 ISSN 0022-5193.
McDonnell, Mark D., Amblard, Pierre-Olivier and Stocks, Nigel G. (2010) Bio-inspired communication: performance limits for information transmission and compression in stochastic pooling networks with binary quantizing nodes. Journal of Computational and Theoretical Nanoscience, Vol.7 (No.5). pp. 876-883. doi:10.1166/jctn.2010.1434 ISSN 1546-1955.
Nikitin, Alexander P., Stocks, Nigel G., Morse, Robert P. and McDonnell, Mark D. (2009) Neural population coding is optimized by discrete tuning curves. Physical Review Letters, Vol.103 (No.13). Article: 138101. doi:10.1103/PhysRevLett.103.138101 ISSN 0031-9007.
McDonnell, Mark D., Amblard, Pierre-Olivier and Stocks, Nigel G. (2009) Stochastic pooling networks. Journal of Statistical Mechanics: Theory and Experiment, Vol.2009 (January 2009). Article: P01012. doi:10.1088/1742-5468/2009/01/P01012 ISSN 1742-5468.
Stocks, Nigel G., McDonnell, Mark D., Morse, Robert P. and Nikitin, Alexander (2009) The role of stochasticity in an information-optimal neural population code. In: International Workshop on Statistical-Mechanical Informatics, Kyoto, Japan, September 13, 2009. Published in: Journal of Physics: Conference Series, Vol.197 Article no. 012015. doi:10.1088/1742-6596/197/1/012015 ISSN 1742-6588.
McDonnell, Mark D. and Stocks, Nigel G. (2008) Maximally informative stimuli and tuning curves for sigmoidal rate-coding neurons and populations. Physical Review Letters, Vol.101 (No.5). doi:10.1103/PhysRevLett.101.058103 ISSN 0031-9007.
McDonnell, Mark D. and Stocks, Nigel G. (2008) Optimal sigmoidal tuning curves for intensity encoding sensory neurons with quasi-Poisson variability. In: Seventeenth Annual Computational Neuroscience Meeting: CNS*2008, Portland, USA, 19-24 Jul 2008. Published in: BMC Neuroscience, Vol.9 (Suppl.1). p. 117. doi:10.1186/1471-2202-9-S1-P117 ISSN 1471-2202.
European Commission (EC)
Daneshkhah, Alireza, Stocks, Nigel G. and Jeffrey, Paul (2017) Probabilistic sensitivity analysis of optimised preventive maintenance strategies for deteriorating infrastructure assets. Reliability Engineering & System Safety, 163 . pp. 33-45. doi:10.1016/j.ress.2017.02.002 ISSN 0951-8320.
Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation (China)] (NSFC)
Durrant, Simon, Kang, Yanmei, Stocks, Nigel G. and Feng, Jianfeng (2011) Suprathreshold stochastic resonance in neural processing tuned by correlation. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), Vol.84 (No.1). Article: 011923. doi:10.1103/PhysRevE.84.011923 ISSN 1539-3755.
Innovate UK
Ahmed, A., Bengherbia, T., Zhvansky, R., Ferrara, G., Wen, J. X. (Jennifer X.) and Stocks, Nigel G. (2016) Validation of geometry modelling approaches for offshore gas dispersion simulations. Journal of Loss Prevention in the Process Industries, 44 . pp. 594-600. doi:10.1016/j.jlp.2016.07.009 ISSN 0950-4230.
Medical Research Council (Great Britain) (MRC)
Morse, Robert P., Allingham, D. and Stocks, Nigel G. (2015) Stimulus-dependent refractoriness in the Frankenhaeuser-Huxley model. Journal of Theoretical Biology, 382 . pp. 397-404. doi:10.1016/j.jtbi.2015.07.002 ISSN 0022-5193.
Morse, Robert P., Allingham, D. and Stocks, Nigel G. (2015) A phenomenological model of myelinated nerve with a dynamic threshold. Journal of Theoretical Biology, 382 . pp. 386-396. doi:10.1016/j.jtbi.2015.06.035 ISSN 0022-5193.
UK Overseas Research Students Awards Scheme (ORSAS)
Yang, Jianhua, Singh, Harsimrat, Hines, Evor, Schlaghecken, Friederike, Iliescu, Daciana, Leeson, Mark S. and Stocks, Nigel G. (2012) Channel selection and classification of electroencephalogram signals: an artificial neural network and genetic algorithm-based approach. Artificial Intelligence In Medicine, Volume 55 (Number 2). pp. 117-126. doi:10.1016/j.artmed.2012.02.001 ISSN 1873-2860.
United States. Office of Naval Research
Nikitin, Alexander P., Bulsara, Adi R. and Stocks, Nigel G. (2017) Enhanced processing in arrays of optimally tuned nonlinear biomimetic sensors : a coupling-mediated Ringelmann effect and its dynamical mitigation. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 95 (3). 032211 . doi:10.1103/PhysRevE.95.032211 ISSN 1539-3755.
University of Sussex
Durrant, Simon, Kang, Yanmei, Stocks, Nigel G. and Feng, Jianfeng (2011) Suprathreshold stochastic resonance in neural processing tuned by correlation. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), Vol.84 (No.1). Article: 011923. doi:10.1103/PhysRevE.84.011923 ISSN 1539-3755.
Warwick Institute of Advanced Study (IAS)
Yang, Jianhua, Singh, Harsimrat, Hines, Evor, Schlaghecken, Friederike, Iliescu, Daciana, Leeson, Mark S. and Stocks, Nigel G. (2012) Channel selection and classification of electroencephalogram signals: an artificial neural network and genetic algorithm-based approach. Artificial Intelligence In Medicine, Volume 55 (Number 2). pp. 117-126. doi:10.1016/j.artmed.2012.02.001 ISSN 1873-2860.
Warwick Postgraduate Research Fellowship (WPRF)
Yang, Jianhua, Singh, Harsimrat, Hines, Evor, Schlaghecken, Friederike, Iliescu, Daciana, Leeson, Mark S. and Stocks, Nigel G. (2012) Channel selection and classification of electroencephalogram signals: an artificial neural network and genetic algorithm-based approach. Artificial Intelligence In Medicine, Volume 55 (Number 2). pp. 117-126. doi:10.1016/j.artmed.2012.02.001 ISSN 1873-2860.
This list was generated on Thu Apr 25 00:05:57 2024 BST.