The State Estimation Problem Of A Kind Of Gene Regulatory Network

Genetic regulatory network is a mechanism regulating gene expression,and it has a great impact on the reproduction,inheritance and variation of organisms.In the biochemical network,these elements regulate each other and balance the evolution of biological system.By studying the state estimation of genetic regulatory networks,we can understand the evolution rules of genes,proteins and small molecules in genetic regulatory networks.In this paper,state estimation of both discrete-time and continuous genetic regulatory networks is discussed respectively.Genetic regulatory network involves discrete and distributed delays,and contains system noise and measurement noise.The main research contents are as follows:In the first chapter,we introduce the research background,the model classification and state estimation of genetic regulatory networksIn the second chapter,we study the problem of state estimation for discrete gene regulatory networks with white noise.In order to save network communication resources,we introduce the event-triggered mechanism in the construction of state estimator.By constructing Lyapunov functional and utilizing some new analytical techniques,sufficient conditions for the ultimate bound of the estimation error system are derived.On this basis,estimator of state estimation is further solved.The numerical simulation verifies the validity of the theoretical results.In the third chapter,we study the state estimation of discrete genetic networks with intermittent outputs.In this case,the network output has a gap,so only part of network output can be collected.The sufficient conditions for an ultimate convergence of the estimation error system are derived by using iterative method the matrix inequality technique.The numerical simulation verifies the validity of the theoretical resultsIn the forth chapter,we study the problem of state estimation for continuous genetic regulatory networks with infinite distributed delays.The event triggering mechanism is introduced into the construction of state estimator.We obtain sufficient conditions for an ultimate bound of the estimation error system and the estimation gain matrix.In addition,by using analytical techniques,we exclude Zeno behavior that may occur in continuous systems.