Research The Stability Of A Class Of Impulse Neural Networks With Mixed Delay And Markov Parameters

With the rapid development of big data technology,neural network has been widely used in the fields of artificial intelligence,associative memory,pattern recognition,signal processing and machine learning.At the same time,it has attracted the attention of scholars and set off a wave of research on neural network.Besides,the artificial neural network will be affected by time delay,impulse and random interference signal in the process of data transmission,so it is an important work to study the stability and state estimation of the neural network in the field of control.In this paper,we study the stability and state estimation of mixed delays Markov impulsive neural network system and mixed delays Markov neutral-type neural network system.Firstly,we introduce event triggering combination into the system to deal with the problem of signal transmission after sampling.Secondly,the sufficient conditions for exponential stability of Markov impulsive neural network system and asymptotic stability of neutral-type system of Markov neural network with mixed delays are obtained by using Lyapunov stability theory,Schur complement lemma and constructing appropriate Lyapunov-Krasovskii functional and using Jensen inequality,improved free weight matrix integral inequality and invert convex inequality.Finally,some examples are simulated by MATLAB LMI toolbox to verify the validity of the results.The main contents and innovations of this thesis can be summarized as follows: 1.In view of the existing markov impulse neural network system with mixed delays in the literature,by changing its Lyapunov-Krasovskii functional structure,pulse system processing method and improving inequality reduction processing technique,a new criterion for the exponential stability of the markov impulse neural network with mixed delays and a larger discrete delay upper bound and a smaller conservative mixed delays are obtained;2.The event triggering mechanism is introduced to study the stability and state estimation of the neutral-type system with mixed time-delay Markov neural network.At the same time,the Lyapunov-Krasovskii functional with augmented term and delayed term is constructed ingeniously,and the sufficient conditions for the asymptotic stability of the neutral-type system with mixed time-delay Markov neural network are obtained.Finally,in the numerical simulation,according to the MATLAB LMI toolbox,the feasibility of the results is verified,and the event trigger matrix and the state feedback control matrix are solved.