
Previous Article
Construction of highly stable implicitexplicit general linear methods
 PROC Home
 This Issue

Next Article
On the virial theorem for nonholonomic Lagrangian systems
Stochastic modeling of the firing activity of coupled neurons periodically driven
1.  Istituto per le Applicazioni del Calcolo CNR, Napoli, Italy 
2.  Dipartimento di Matematica e Applicazioni, Università di Napoli Federico II, Via Cintia, Napoli 
References:
show all references
References:
[1] 
Massimiliano Tamborrino. Approximation of the first passage time density of a Wiener process to an exponentially decaying boundary by twopiecewise linear threshold. Application to neuronal spiking activity. Mathematical Biosciences & Engineering, 2016, 13 (3) : 613629. doi: 10.3934/mbe.2016011 
[2] 
Marie Levakova. Effect of spontaneous activity on stimulus detection in a simple neuronal model. Mathematical Biosciences & Engineering, 2016, 13 (3) : 551568. doi: 10.3934/mbe.2016007 
[3] 
Qiuying Li, Lifang Huang, Jianshe Yu. Modulation of firstpassage time for bursty gene expression via random signals. Mathematical Biosciences & Engineering, 2017, 14 (5&6) : 12611277. doi: 10.3934/mbe.2017065 
[4] 
Vincent Renault, Michèle Thieullen, Emmanuel Trélat. Optimal control of infinitedimensional piecewise deterministic Markov processes and application to the control of neuronal dynamics via Optogenetics. Networks & Heterogeneous Media, 2017, 12 (3) : 417459. doi: 10.3934/nhm.2017019 
[5] 
Vladimir Kazakov. Sampling  reconstruction procedure with jitter of markov continuous processes formed by stochastic differential equations of the first order. Conference Publications, 2009, 2009 (Special) : 433441. doi: 10.3934/proc.2009.2009.433 
[6] 
Jiaqin Wei, Zhuo Jin, Hailiang Yang. Optimal dividend policy with liability constraint under a hidden Markov regimeswitching model. Journal of Industrial & Management Optimization, 2017, 13 (5) : 110. doi: 10.3934/jimo.2018132 
[7] 
Karoline Disser, Matthias Liero. On gradient structures for Markov chains and the passage to Wasserstein gradient flows. Networks & Heterogeneous Media, 2015, 10 (2) : 233253. doi: 10.3934/nhm.2015.10.233 
[8] 
Yinghui Dong, Kam Chuen Yuen, Guojing Wang. Pricing credit derivatives under a correlated regimeswitching hazard processes model. Journal of Industrial & Management Optimization, 2017, 13 (3) : 13951415. doi: 10.3934/jimo.2016079 
[9] 
Martin Heida, Alexander Mielke. Averaging of timeperiodic dissipation potentials in rateindependent processes. Discrete & Continuous Dynamical Systems  S, 2017, 10 (6) : 13031327. doi: 10.3934/dcdss.2017070 
[10] 
Wael Bahsoun, Paweł Góra. SRB measures for certain Markov processes. Discrete & Continuous Dynamical Systems  A, 2011, 30 (1) : 1737. doi: 10.3934/dcds.2011.30.17 
[11] 
Mathias Staudigl. A limit theorem for Markov decision processes. Journal of Dynamics & Games, 2014, 1 (4) : 639659. doi: 10.3934/jdg.2014.1.639 
[12] 
Artur Stephan, Holger Stephan. Memory equations as reduced Markov processes. Discrete & Continuous Dynamical Systems  A, 2019, 39 (4) : 21332155. doi: 10.3934/dcds.2019089 
[13] 
Linyi Qian, Wei Wang, Rongming Wang. Riskminimizing portfolio selection for insurance payment processes under a Markovmodulated model. Journal of Industrial & Management Optimization, 2013, 9 (2) : 411429. doi: 10.3934/jimo.2013.9.411 
[14] 
Zhenzhong Zhang, Enhua Zhang, Jinying Tong. Necessary and sufficient conditions for ergodicity of CIR model driven by stable processes with Markov switching. Discrete & Continuous Dynamical Systems  B, 2018, 23 (6) : 24332455. doi: 10.3934/dcdsb.2018053 
[15] 
Aniello Buonocore, Luigia Caputo, Enrica Pirozzi, Maria Francesca Carfora. Gaussdiffusion processes for modeling the dynamics of a couple of interacting neurons. Mathematical Biosciences & Engineering, 2014, 11 (2) : 189201. doi: 10.3934/mbe.2014.11.189 
[16] 
WeiJian Bo, Guo Lin. Asymptotic spreading of time periodic competition diffusion systems. Discrete & Continuous Dynamical Systems  B, 2018, 23 (9) : 39013914. doi: 10.3934/dcdsb.2018116 
[17] 
H.Thomas Banks, Shuhua Hu. Nonlinear stochastic Markov processes and modeling uncertainty in populations. Mathematical Biosciences & Engineering, 2012, 9 (1) : 125. doi: 10.3934/mbe.2012.9.1 
[18] 
Xian Chen, ZhiMing Ma. A transformation of Markov jump processes and applications in genetic study. Discrete & Continuous Dynamical Systems  A, 2014, 34 (12) : 50615084. doi: 10.3934/dcds.2014.34.5061 
[19] 
A. M. Vershik. Polymorphisms, Markov processes, quasisimilarity. Discrete & Continuous Dynamical Systems  A, 2005, 13 (5) : 13051324. doi: 10.3934/dcds.2005.13.1305 
[20] 
Ka Chun Cheung, Hailiang Yang. Optimal investmentconsumption strategy in a discretetime model with regime switching. Discrete & Continuous Dynamical Systems  B, 2007, 8 (2) : 315332. doi: 10.3934/dcdsb.2007.8.315 
Impact Factor:
Tools
Metrics
Other articles
by authors
[Back to Top]