Priscilla E. Greenwood
Affiliations: | Applied Mathematics for the Life and Social Sciences | Arizona State University, Tempe, AZ, United States |
Area:
Applied Mathematics, Neuroscience BiologyGoogle:
"Priscilla Greenwood"Parents
Sign in to add mentorJoshua Chover | grad student | 1963 | UW Madison | |
(The Convolution Equation Over a Compact Real Interval for Some Special Kernels) |
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Publications
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Mata MA, Tyson RC, Greenwood P. (2019) Random fluctuations around a stable limit cycle in a stochastic system with parametric forcing. Journal of Mathematical Biology. 79: 2133-2155 |
Lee W, Greenwood PE, Heckman N, et al. (2016) Pre-averaged kernel estimators for the drift function of a diffusion process in the presence of microstructure noise Statistical Inference For Stochastic Processes. 20: 237-252 |
Greenwood PE, McDonnell MD, Ward LM. (2015) Dynamics of gamma bursts in local field potentials. Neural Computation. 27: 74-103 |
Rowat PF, Greenwood PE. (2014) The ISI distribution of the stochastic Hodgkin-Huxley neuron. Frontiers in Computational Neuroscience. 8: 111 |
Bani R, Hameed R, Szymanowski S, et al. (2013) Influence of environmental factors on college alcohol drinking patterns. Mathematical Biosciences and Engineering : Mbe. 10: 1281-300 |
Ditlevsen S, Greenwood P. (2013) The Morris-Lecar neuron model embeds a leaky integrate-and-fire model. Journal of Mathematical Biology. 67: 239-59 |
Mubayi A, Greenwood PE. (2013) Contextual Interventions for Controlling Alcohol Drinking Mathematical Population Studies. 20: 27-53 |
Rowat PF, Greenwood PE. (2011) Identification and continuity of the distributions of burst-length and interspike intervals in the stochastic Morris-Lecar neuron. Neural Computation. 23: 3094-124 |
Giraudo MT, Greenwood PE, Sacerdote L. (2011) How sample paths of leaky integrate-and-fire models are influenced by the presence of a firing threshold. Neural Computation. 23: 1743-67 |
Mubayi A, Greenwood P, Wang X, et al. (2011) Types of drinkers and drinking settings: an application of a mathematical model. Addiction (Abingdon, England). 106: 749-58 |