Event-triggered H ∞ state estimation for discrete-time stochastic genetic regulatory networks with Markovian jumping parameters and time-varying delays.
Qi LiBo ShenYurong LiuFuad E. AlsaadiPublished in: Neurocomputing (2016)
Keyphrases
- state estimation
- state space model
- genetic regulatory networks
- dynamic systems
- kalman filter
- ordinary differential equations
- kalman filtering
- maximum likelihood
- markov chain
- particle filter
- particle filtering
- visual tracking
- expectation maximization
- reverse engineering
- data sets
- parameter estimation
- search space
- data analysis