Pubblications - Laura Sacerdote

Laura Sacerdote
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Research
    1. Gilat, D., Meilijson, I. and Sacerdote, L. (2020) A sharp bound on expected local time of a continuous L^2-bounded Martingale (submitted) ArXiv
    2. De Ambroggio, U., Polito, F. and Sacerdote, L. (2020) On Dynamic random Graphs with Degree Homogenization via anti-preferential attachment probabilities. (submitted) ArXiv
    3. Pachon A., Polito F. , Sacerdote L. (2020), On the continuous-time limit of the Barabási-Albert random graph Applied Mathematics and Computation (to appear) ArXiv
    4. Christodoulou, C., Kostal, L., Sacerdote, L. (2020) Preface BioSystems 187,104049
    5. Kostal, L., Sacerdote, L., Tamborrino, M. (2019)  Preface: Special issue: Neural coding 2018; Mathematical Biosciences and Engineering 16(6), pp. 8214-8216
    6. Verzelli, P. Sacerdote L. (2019) A study of dependency features of spike trains through copulas BioSystems BIO_104014 DOI information: 10.1016/j.biosystems.2019.104014
    7. Pachon, A., Sacerdote, L. and Yang, S. (2018) Scale-free behavior of networks with the copresence of preferential and uniform attachment rules Physica D, 371, 1-12
    8. Gilat, D., Meilijson, I. and Sacerdote, L. (2018) A sharp bound for the expected number of upcrossings of an L_2-bounded martingale. Stochastic Processes and their applications Vol 128, 6 Pages 1849-1856 DOI: 10.1016/j.spa.2017.08.012
    9. Halabi, A. Kenett, R. and Sacerdote, L. (2018) Modeling the Relationship Between Reliability Assessment and Risk Predictors Using Bayesian Networks and a Multiple Logistic Regression Model. Quality Engineering 30(4), pp. 663-675
    10. Halabi, A. Kenett, R. and Sacerdote L. (2017) Using dynamic Bayesian networks to model technical risk
      management efficiency Qual Reliab Eng. Int,Vol 33 Issue 6 1179-1196
    11. Andreis, L. Polito, F. and Sacerdote, L On a class of Time-fractional Continuous-state Branching Processes. Markov Processes and Related Fields, Vol. 23 (4), 591-607, 2017.  ArXiv
    12. P. Lansky, Polito F. and Sacerdote L. (2016) Generalized Nonlinear Yule Models Journal of Statistical Physics 162 (6), 1608-1638, 2016 ArXiv
    13. P. Lansky, Sacerdote L. and Zucca C.  (2016) The Gamma renewal process as an output of the diffusion leaky integrate-and-fire neuronal model Biol. Cybern. Volume 110, Issue 2, pp 193–200
    14. Pachon, A., Polito, F. and Sacerdote, L. (2016) Random Graphs Associated to some Discrete and Continuous Time Preferential Attachment Models  J. of Statistical Physics. Volume 162, Issue 6, pp 1608–1638 ArXiv
    15. Sacerdote, L., Tamborrino, M. and Zucca, C. (2016) First passage times for two-dimensional correlated diffusion processes: analytical and numerical methods.
      J. Computational Applied Mathematics
      Volume 296, Pages 275–292.
      ArXiv
    16. Bibbona, E. Sacerdote, L. and Torre, E. (2016)
      A copula-based method to build diffusion models with prescribed marginal and serial dependence
      Methodology and Computing in Applied Probability
      18(3), pp. 765-783
      ArXiv
    17. Benedetto,E., Polito  F. and Sacerdote L. (2015) On Firing Rate Estimation for Dependent Interspike Intervals Neural  Computation, Vol. 27 (3), 699-724. ArXiv
    18. Tamborrino, M., Sacerdote, L. and Jacobsen, M. (2014) Weak convergence of marked point processes generated by crossings of multivariate jump processes. Application to neural network modeling. Physica D, 288, 45-52.
    19. P. Lansky, Polito F. and Sacerdote L. (2014) The role of detachment of in-links in scale-free networks. J. of Physics A- Mathematical and theoretical 47, (34) ArXiv
    20. Sacerdote, L. and Zucca, C. (2013) Joint distribution of first exit times of a two dimensional Wiener process with jumps with application to a pair of coupled neurons Math. Biosc. Volume 245, Issue 1, Pages 61–69
    21. L. Sacerdote, O. Telve and C. Zucca (2013)  Joint densities of first passage times of a diffusion process through two constant boundaries. Journal of Advanced Applied Probability,  4, (1) 186-202 ArXiv
    22. Sirovich, R. Sacerdote L. and Villa A.E.P. (2013) Cooperative behavior in a jump diffusion model for a simple network of spiking neurons Math. Biosc. for Engineering, 11, n.2 385-401
    23. Benedetto, E.,  Sacerdote L. (2013) : On dependency properties of the ISIs generated by a two-compartmental neuronal model. Biological Cybernetics 107(1): 95-106  Aperto
    24. Benedetto E., Sacerdote, L. and Zucca C. (2013)  : A first passage problem for a bivariate diffusion process: Numerical solution with an application to neuroscience when the process is Gauss-Markov. J. Computational Applied Mathematics 242: 41-52  ArXiv
    25. Sacerdote L. and Giraudo M.T. (2013): Stochastic Integrate and Fire Models: a Review on Mathematical Methods and their Applications Stochastic Biomathematical Models with Applications to Neuronal Modeling.   Lecture Notes in Mathematics series (Biosciences subseries), 2058: 99-142 Bachar, Batzel and Ditlevsen (Eds.),Springer,  ArXiv
    26. Sacerdote, L., Tamborrino, M. and Zucca, C. (2012) Detecting dependencies between spike trains of pairs of neurons through copulas. Brain Research, Vol. 1434: 243-256. ArXiv
    27. Giraudo, M.T., Greenwood P. and Sacerdote L. (2011) How sample paths of Leaky Integrate and Fire models are influenced by the presence of a firing threshold. Neural Computation Vol. 23, No. 7, Pages 1743-1767
    28. Bonino,D., Gai,  M. and Sacerdote, L. (2010) Statistical techniquesfor interferometric signal analysis. Mem. S.A. It. 75, 283
    29. Sacerdote, L. and Sirovich R. (2010) A copulas approach to neuronal networks models. Journal of Physiology- Paris Volume 104, Issues      3-4, Pages 223-230 Aperto
    30. Sacerdote, L. and Tamborrino M.  (2010) Leaky Integrate and Fire models coupled through copulas: association properties of the Interspikes Intervals. Chinese Journal of Physiology.2010 Dec 31;53(6):396-406
    31. Zucca, C.  and  Sacerdote,  L. (2009) On the Inverse First-Passage-Time Problem for a Wiener Process Annals of Applied Probability, 19, 4, 1319-1346 ArXiv
    32. Giraudo, M.T., Mininni R. and Sacerdote, L. (2009) On the Asymptotic Bahaviour of the Parameter Estimators for Some Diffusion Processes Application to Neuronal Models. Ricerche di Matematica.58, 103-127, DOI 10.1007/s11587-009-0050-4. Online ISSN 0035-5038 Journal Volume Volume 58, Number 1
    33. Bibbona, E., Lansky, P.,  Sacerdote L. and R. Sirovich (2008) Errors in estimation of the input signal for integrate and fire neuronal models. PHYSICAL REVIEW E 78, 01 011918-1- 011918-10 Aperto
    34. Giraudo, M.T.,Sacerdote, L. and Sirovich R. (2008) Information measures in a small network of spiking neurons. Scientiae Mathematicae Japonicae 67 (2) 191-204
    35. Giraudo M.T., Sacerdote L. and Sicco A. (2007) Ghost Stochastic Resonance for a neuron with a couple of periodic inputs Lecture Notes in Computer Science 4729,
    36. Lansky, P.,Sacerdote, L. and Zucca C. (2007) Input identification in the Ornstein-Uhlenbeck neuronal model with signal dependent noise Lecture Notes in Computer Science 4729, pp. 368–377,
    37. Sirovich, R., Sacerdote, L., Villa, A.E.P.(2007) Effect of increasing inhibitory inputs on information processing within a small network of spiking neurons, Lecture Notes in Computer Science 4507: 23-30,
    38. Lansky, P., Sacerdote, L. and Zucca, C. (2007) Optimum signal in a diffusion leaky integrate-and-fire neuronal model. Math. Biosc.vol. 68, pp. 1257-1264 ISSN: 0092-8240.
    39. Giraudo, M.T. and Sacerdote, L. (2006) Ghost stochastic resonance for a stochastic single neuron model. Scientiae Mathematicae Japonicae.    64 n.2 299-312
    40. Sacerdote, L., Villa A.E.P. and Zucca C. (2006) On the classification of experimental data modeled via a stochastic leaky integrate and fire model through boundary values. Bull. Math. Biol. 68(6):1257-74
    41. Villa, A. E.P., Sacerdote, L. and Farina, A. (2005) Preface. BioSystems 79, 1-2
    42. Giraudo, M.T. and Sacerdote, L. (2004) Effect of periodic stimulus on a neuronal diffusion model with signal-dependent noise. BioSystems 79,      Issue 1-3, 73-81
    43. Sacerdote, L. and Smith, C.E. (2004) Almost sure comparisons for first passage times of diffusion processes through boundaries. Methodology and Computing in Applied Probability 6, Number 3, 323-341
    44. Lansky, P., Rodriguez, R. and Sacerdote, L. (2004) Mean instantaneous firing frequency is always higher than the firing rate. Neural Computation. Number 16, 477-489. Preprint
    45. Sacerdote, L. and Zucca, C. (2003) Threshold shape corresponding to a Gamma firing distribution in an Ornstein-Uhlenbeck neuronal model. Scientiae Mathematicae Japonicae. 58-2, 295-306.
    46. Sacerdote, L. and Sirovich, R. (2003) Multimodality of the interspike interval distribution in a simple jump-diffusion model Scientiae Mathematicae Japonicae. 58-2, 307-321.
    47. Galleani, G., Sacerdote, L., Tavella, P. and Zucca, C. (2003) A mathematical model for the atomic clock error. Metrologia 40, 257-264. ArXiv
    48. Giraudo,  M.T., Sacerdote, L. and Sirovich, R. (2002) Effects of random jumps on a very simple neuronal diffusion model. BioSystems. 67,  Issues 1-3
    49. Lansky, P. and Sacerdote, L. (2002) Interspike interval statistics in the Ornstein-Uhlenbeck neuronal model with signal-dependent noise. BioSystems. 67, Issues 1-3, 213-219
    50. Lansky, P. and Sacerdote, L. (2001) The Ornstein-Uhlenbeck neuronal model with the signal-dependent noise. Physics Letters A 285, 132-140
    51. Giraudo,  M.T., Sacerdote, L. and Zucca, C. (2001) A Monte Carlo Method for the Simulation of First Passage Times of Diffusion Processes Meth. Comp. Appl. Prob. 3, 215-231
    52. Sacerdote, L. and Smith, C.E. (2000) New Parameter Relationships Determined Via Stochastic Ordering for Spike Activity in a Reversal Potential Model. BioSystem      58: 59-65. Preprint
    53. Sacerdote,  L. and Smith, C.E. (2000) A qualitative comparison of some diffusion models for neural activity via stochastic ordering. Biol.      Cybernetics 83, 6 543-551.
    54. Giraudo,  M.T. and Sacerdote, L. (1999) An improved technique for the simulation of first passage times for diffusion processes Communication in Statistics: simulation and computation. 28, n.4, 1135-1163
    55. Giraudo, M.T. and Sacerdote, L. (1998) Simulation methods in neuronal modeling. BioSystems, Elsevier, 48, 77-83.
    56. Giraudo, M.T. and Sacerdote, L. (1997) Jump-Diffusion processes as models for  neuronal activity. Biosystems 40,75-82
    57. Sacerdote,      L. and Tomassetti, F. (1996) On the evaluation and asymptotic approximations for first-passage-time probabilities. Adv.      Appl. Prob. 28, 270-284
    58. Lansky,  P., Sacerdote, L. and Tomassetti, F. (1995) On the comparison of Feller and Ornstein-Uhlenbeck Models for Neural Activity. Biol. Cyb. 73, 457-465
    59. Sacerdote, L. and Ricciardi, L.M. (1992) On the transformation of diffusion equations into the Kolmogorov equation for the Wiener process. Ricerche di Matematica. Vol. XLI fasc., 1123-135
    60. Balossino, N., Buonocore, N. and Sacerdote, L. (1992) On two neuronal diffusion models. Cyb. and Systems ‘92. Trappl R.. ed.
    61. Sacerdote, L. (1990) Asymptotic behaviour of Ornstein-Uhlenbeck first-passage-time density through periodic boundaries. Appl. Stoch. Models and Data Analysis. 6, 53-57
    62. Sacerdote, L. (1990) On the solution of the Fokker-Plank equation for Feller process. Adv. Appl. Prob. 22, 101-110
    63. Ricciardi, L.M. and Sacerdote, L. (1987) On the probability densities of an Ornstein- Uhlenbeck process with a reflecting boundary. J. Appl.      Prob. 24, 355-369
    64. Giorno, V., Nobile, A.G., Ricciardi, L.M. and Sacerdote, L. (1986) Some remarks on the Rayleigh process. J. Appl. Prob. 23 , 398-408
    65. Nobile, A.G., Ricciardi, L.M. and Sacerdote, L. (1985) Exponential trends for a class of diffusion processes with steady state distribution. J. Appl. Prob. 22, 611-618
    66. Nobile, A.G., Ricciardi, L.M. and Sacerdote, L. (1985) Exponential trends of Ornstein- Uhlenbeck first-passage-time densities. J. Appl. Prob. 22, 360-369
    67. Nobile, A.G., Ricciardi, L.M. and Sacerdote, L. (1985) A note on first-passage-time problems. J. Appl. Prob. 22, 346-359
    68. Balossino, N., Ricciardi, L.M. and Sacerdote, L. (1985) Evaluation of  first-passage-time densities for diffusion processes. Cyb. and Systems 16, 325-339
    69. Ricciardi, L.M. and Sacerdote, L. and Sato, S. (1984) On an integral equation for first passage time probability density function. J. Appl. Prob. 21, 302-314
    70. Ricciardi, L.M. and Sacerdote, L. and Sato, S. (1983) Diffusion approximation and first passage time problem for a model neuron. Math. Biosc. 64, 29-44
    71. Nobile, A.G., Ricciardi, L.M. and Sacerdote, L. (1982) On Gompertz growth model and related difference equations. Biol. Cyb. 42, 221-229
    72. Favella, L., Reineri, M.T., Ricciardi, L.M. and Sacerdote, L. . (1982) First-passage-time problems and some related      computational methods. Cyb. and Systems 13, 95-128
    73. Cerbone,  G., Ricciardi, L.M. and Sacerdote, L. (1981) Mean Variance and Skewness of first passage time for the Ornstein-Uhlenbeck process. Cyb. and Systems 12, 395-429
    74. Ricciardi, L.M. and Sacerdote, L. (1979) The Ornstein-Uhlenbeck process as a model for neuronal activity. Biol.Cyb. 35, 1-9

    Refereed Proceedings
    1. Sacerdote, L., Garetto, M., Polito, F. and Sereno, M. (2013) Superprocesses as models for information dissemination in the future internet. Proceedings of Mathematical Models and Methods for Planet Earth, 157-170, Springer, 2014. ArXiv
    2. Sacerdote L., Zucca C. (2007). Statistical study of the Inverse First Passage Time Algorithm. In: Spie: fluctuations and noise. Spie Fluctuations and Noise. 21-24 Maggio 2007. : Leon Coen ed.
    3. Sacerdote L., Tavella P. (2007). Roles of noise in reliability problems: the view point of a mathematician and some application proposals. In: Edited by Cohen, Leon. Proceedings of the SPIE, Volume 6603, pp. 66030Y (2007). Spie Fluctuations and Noise. 21-24 Maggio 2007. (vol. 6603, pp. 66030-66038). : Leon Coen ed.
    4. Sacerdote, L. , Sirovich, R. and Zucca, C. (2005) Stochastic leaky integrate and fire neuronal model: examples of its application to neuronal coding study. Industrial days. ESCULAPIO Pub. Co. Aquilano et. al. Eds
    5. L. Sacerdote, A and C. Zucca (2005) Inverse first passage time method in the analysis of neuronal interspike intervals of neurons characterized by time varying dynamics. LNCS 3704, Springer Verlag, De Gregorio et al. Ed. 69-77
    6. Sacerdote, L. and Sirovich, R. (2004) Noise induced phenomena in jump diffusion models for single neuron spike activity. IJCNN Proceedings, Budapest 2004
    7. Sacerdote, L. and Zucca, C. (2003) On the relationship between interspikes interval distribution and boundary shape in the Ornstein-Uhlenbeck neuronal model. EMCTB Proceedings. V. Capasso ed., 161-168
    8. Sacerdote, L. and Sirovich, R. (2003) A Wiener process with inverse Gaussian time distributed jumps as a model for neuronal activity. EMCTB Proceedings. V. Capasso ed. 134-140
    9. Cascino, B. Galleani, L., Gallo, G. Sacerdote, L., Tavella, P. and Zucca, C. (2002) The Mathematical model of the atomic clock error: an overview. Proceedings of the 4th time scales Algorithms Symposium at Bureau International des Poids et Measures. Paris, March 2002
    10. Giraudo, M.T. and Sacerdote, L. (1996) Some remarks on First-Passage-Time for Jump- Diffusion Processes. In Cybernetics and Systems ‘96. R. Trappl ed. 518-523
    11. Sacerdote, L. and Tomassetti, F. (1994) On the comparison of different neural models. Cybernetics and Systems‘94. Trappl, R. ed. World Scient. Comp.Comp 815-822
    12. Balossino, N., Buonocore, N. and Sacerdote, L. (1992) On two neuronal diffusion models. Cyb. and Systems ‘92. Trappl R.. ed.
    13. Sacerdote, L. (1988) Some remarks on first-passage-time problems.In: Biomathematics and related Computational Problems. Ricciardi, L.M. ed. Reidel Pub. Comp. 567-579
    14. Sacerdote, L. (1988)On Neuronal modelling and first-passage-time problems In: Cyb. and Systems Trappl, R. ed. Kluwer Ac. Pub. 359-366
    15. Nobile, A.G. Ricciardi, L.M. and Sacerdote, L. (1984) On a class of discrete models for regulated growth with intrinsic lower bounds. Cyb. and Systems Res. 2 Trappl R. ed. North Holland Pub. Comp.
    16. Nobile, A.G., Ricciardi, L.M. and Sacerdote, L. (1982) On a class of difference equations modeling growth processes. Biomath. in 1980 Scott A. and Ricciardi, L.M. ed. North Holland Math. Pub. 217-243
     
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