JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Design of Time-varying Stochastic Process with Dynamic Bayesian Networks
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Design of Time-varying Stochastic Process with Dynamic Bayesian Networks
Cho, Hyun-Cheol; Fadali, M.Sami; Lee, Kwon-Soon;
  PDF(new window)
 Abstract
We present a dynamic Bayesian network (DBN) model of a generalized class of nonstationary birth-death processes. The model includes birth and death rate parameters that are randomly selected from a known discrete set of values. We present an on-line algorithm to obtain optimal estimates of the parameters. We provide a simulation of real-time characterization of load traffic estimation using our DBN approach.
 Keywords
Adaptive estimation;Birth-Death process;Convergence property;Dynamic Bayesian networks;
 Language
English
 Cited by
1.
Dynamic Bayesian modelling of non-stationary stochastic systems using constrained least square estimation and gradient descent optimisation, IET Signal Processing, 2012, 6, 6, 608  crossref(new windwow)
2.
Fault Detection and Isolation of Induction Motors Using Recurrent Neural Networks and Dynamic Bayesian Modeling, IEEE Transactions on Control Systems Technology, 2010, 18, 2, 430  crossref(new windwow)
 References
1.
I. Zeifman, 'General Birth-death processes and simple stochastic epidemic models,' Automation and Remote Control, vol. 46, no. 6, pp. 789-795, 1985

2.
S. Blaabjerg and H. Andersson, 'Approximating the heterogeneous fluid queue with a birth-death fluid queue,' IEEE Trans. on Communications, vol. 43, no. 5, pp. 1884-1887, 1995 crossref(new window)

3.
M. Alonso and F. J. Alguacil, 'Stochastic modeling of particle coating.' AIChE Journal, vol. 47, no. 6, pp. 1303-1308, 2001 crossref(new window)

4.
S. C. Kou, 'Modeling growth stocks via birth-death processes,' Advances in Applied Probability, vol. 35, no. 3, pp. 641-664, 2003 crossref(new window)

5.
P. R. Parthasarathy and K. V. Vijayashree, 'Fluid queues driven by birth and death processes with quadratic rates,' International Journal of Computer Mathematics, vol. 80, no. 11, pp. 1385-1395, 2003 crossref(new window)

6.
V. Rykov, 'Generalized birth-death processes and their application to the ageing models,' Automation and Remote Control, vol. 67, no. 3, pp. 435-451, 2006 crossref(new window)

7.
K. Murphy, 'Dynamic Bayesian networks: Representation, Inference and Learning.' Ph.D. Dissertation, UC Berkeley, 2002

8.
J. N. Daigle, Queuing theory with applications to packet telecommunication, New York, Springer, 2005

9.
J. M. Mendel, Lessons in estimation theory for signal processing, communications, and control, New Jersey, Prentice Hall, 1995

10.
W. J. Rugh, Linear system theory, Prentice Hall, 1996

11.
Y.-H. Wen, T-T Lee, and H-J Cho, 'Hybrid Greybased recurrent neural networks for short-term traffic forecasting and dynamic travel time estimation,' IEEE Conference on Intelligent Transportation Systems, 2005