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Original Articles

An improved technique for the simulation of first passage times for diffusion processes

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Pages 1135-1163 | Received 01 Jan 1998, Published online: 27 Jun 2007

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Pak-Wing Fok. (2013) Drift reconstruction from first passage time data using the Levenberg–Marquardt method. Inverse Problems in Science and Engineering 21:8, pages 1288-1309.
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Articles from other publishers (28)

S. Herrmann & C. Zucca. (2019) Exact Simulation of the First-Passage Time of Diffusions. Journal of Scientific Computing 79:3, pages 1477-1504.
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Qinglai Dong & Lirong Cui. (2018) First Hitting Time Distributions for Brownian Motion and Regions with Piecewise Linear Boundaries. Methodology and Computing in Applied Probability 21:1, pages 1-23.
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Wilhelm Braun, Rüdiger Thul & André Longtin. (2017) Evolution of moments and correlations in nonrenewal escape-time processes. Physical Review E 95:5.
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Francisco Bernal & Juan A. Acebrón. (2016) A Comparison of Higher-Order Weak Numerical Schemes for Stopped Stochastic Differential Equations. Communications in Computational Physics 20:3, pages 703-732.
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Massimiliano Tamborrino. (2016) Approximation of the first passage time density of a Wiener process to an exponentially decaying boundary by two-piecewise linear threshold. Application to neuronal spiking activity. Mathematical Biosciences and Engineering 13:3, pages 613-629.
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S. Herrmann & E. Tanré. (2016) The First-passage Time of the Brownian Motion to a Curved Boundary: an Algorithmic Approach. SIAM Journal on Scientific Computing 38:1, pages A196-A215.
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Christos H. Skiadas & Charilaos Skiadas. (2014) Exploring the State of a Stochastic System via Stochastic Simulations: An Interesting Inversion Problem and the Health State Function. Methodology and Computing in Applied Probability 17:4, pages 973-982.
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Wilhelm Braun, Paul C. Matthews & Rüdiger Thul. (2015) First-passage times in integrate-and-fire neurons with stochastic thresholds. Physical Review E 91:5.
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Laura Sacerdote, Ottavia Telve & Cristina Zucca. (2016) Joint Densities of First Hitting Times of a Diffusion Process Through Two Time-Dependent Boundaries. Advances in Applied Probability 46:1, pages 186-202.
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Roberta Sirovich, Laura Sacerdote & Alessandro E. P. Villa. (2014) Cooperative behavior in a jump diffusion model for a simple network of spiking neurons. Mathematical Biosciences and Engineering 11:2, pages 385-401.
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Aniello Buonocore, Luigia Caputo, Enrica Pirozzi & Maria Francesca Carfora. (2014) A simple algorithm to generate firing times for leaky integrate-and-fire neuronal model. Mathematical Biosciences and Engineering 11:1, pages 1-10.
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ENRICO BIBBONA & SUSANNE DITLEVSEN. (2012) Estimation in Discretely Observed Diffusions Killed at a Threshold. Scandinavian Journal of Statistics 40:2, pages 274-293.
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Elisa Benedetto, Laura Sacerdote & Cristina Zucca. (2013) A first passage problem for a bivariate diffusion process: Numerical solution with an application to neuroscience when the process is Gauss–Markov. Journal of Computational and Applied Mathematics 242, pages 41-52.
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Laura Sacerdote & Maria Teresa Giraudo. 2013. Stochastic Biomathematical Models. Stochastic Biomathematical Models 99 148 .
Pavel Chigansky & Fima C. Klebaner. (2012) The Euler-Maruyama approximation for the absorption time of the CEV diffusion. Discrete & Continuous Dynamical Systems - B 17:5, pages 1455-1471.
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Maria Teresa Giraudo, Priscilla E. Greenwood & Laura Sacerdote. (2011) How Sample Paths of Leaky Integrate-and-Fire Models Are Influenced by the Presence of a Firing Threshold. Neural Computation 23:7, pages 1743-1767.
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Enrico Bibbona, Petr Lansky & Roberta Sirovich. (2010) Estimating input parameters from intracellular recordings in the Feller neuronal model. Physical Review E 81:3.
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Maria Teresa Giraudo, Rosa Maria Mininni & Laura Sacerdote. (2009) On the asymptotic behavior of the parameter estimators for some diffusion processes: application to neuronal models. Ricerche di Matematica 58:1, pages 103-127.
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Enrico Bibbona, Gianna Panfilo & Patrizia Tavella. (2008) The Ornstein–Uhlenbeck process as a model of a low pass filtered white noise. Metrologia 45:6, pages S117-S126.
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Enrico Bibbona, Petr Lansky, Laura Sacerdote & Roberta Sirovich. (2008) Errors in estimation of the input signal for integrate-and-fire neuronal models. Physical Review E 78:1.
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Liqun Wang & Klaus Pötzelberger. (2007) Crossing Probabilities for Diffusion Processes with Piecewise Continuous Boundaries. Methodology and Computing in Applied Probability 9:1, pages 21-40.
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Laura Sacerdote, Cristina Zucca & Petr Láanskáy. 2007. Advances in Brain, Vision, and Artificial Intelligence. Advances in Brain, Vision, and Artificial Intelligence 368 377 .
Susanne Ditlevsen & Petr Lansky. (2005) Estimation of the input parameters in the Ornstein-Uhlenbeck neuronal model. Physical Review E 71:1.
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F.M. Buchmann. (2005) Simulation of stopped diffusions. Journal of Computational Physics 202:2, pages 446-462.
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Maria Teresa Giraudo & Laura Sacerdote. (2005) Effect of periodic stimulus on a neuronal diffusion model with signal-dependent noise. Biosystems 79:1-3, pages 73-81.
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Laura Sacerdote & Cristina Zucca. 2005. Brain, Vision, and Artificial Intelligence. Brain, Vision, and Artificial Intelligence 69 77 .
Laura Sacerdote & Petr Lánský. (2002) Interspike interval statistics in the Ornstein–Uhlenbeck neuronal model with signal-dependent noise. Biosystems 67:1-3, pages 213-219.
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Petr Lánský & Laura Sacerdote. (2001) The Ornstein–Uhlenbeck neuronal model with signal-dependent noise. Physics Letters A 285:3-4, pages 132-140.
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