State estimation of reaction–diffusion impulse genetic regulatory networks with semi-Markovian jump parameters

This paper focuses on a class of state estimation problems for impulse genetic regulatory networks with reaction– diffusion terms. First, considering the influence of environment on the target systems, a semi-Markovian jump process is used to model the genetic regulatory networks. In addition, considering the activation and repression of transcription factors and the transient nature of signaling, an impulse signal is also employed to model the studied networks. Furthermore, a novel space-dividing measurement method is used to reduce the estimator design cost. Finally, the effectiveness of the designed state estimator is verified based on numerical examples.