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Design of Time-varying Stochastic Process with Dynamic Bayesian Networks

  • Published : 2007.12.31

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

References

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  1. Dynamic Bayesian modelling of non-stationary stochastic systems using constrained least square estimation and gradient descent optimisation vol.6, pp.6, 2012, https://doi.org/10.1049/iet-spr.2010.0081
  2. Fault Detection and Isolation of Induction Motors Using Recurrent Neural Networks and Dynamic Bayesian Modeling vol.18, pp.2, 2010, https://doi.org/10.1109/TCST.2009.2020863