Particle Filtering Approach To State Estimation In Boolean Dynamical Systems Conference Paper uri icon

abstract

  • Exact optimal state estimation for discrete-time Boolean dynamical systems may become impractical computationally if system dimensionality is large. In this paper, we consider a particle filtering approach to address this problem. The methodology is illustrated through application to state tracking in high-dimensional Boolean network models. The results show that the particle filter can be very accurate under a moderate number of particles. The impact of resampling on performance is also investigated. © 2013 IEEE.

author list (cited authors)

  • Braga-Neto, U.

citation count

  • 5

publication date

  • December 2013

publisher