Research On Synchronization Of Time Delays Stochastic Neural Network Model

Neural networks model the process of information processing in real society by simulating the transfer characteristics of neural impulses between biological neurons.These processes are superimposed on each other to form a complex and large-scale nonlinear dynamic system.In recent years,neural networks have developed rapidly and have played an important role in many fields,such as pattern recognition and signal processing.From this we can see that the neural network has a very broad prospect,and therefore has attracted the attention of a large number of experts and scholars,and has gradually become an important hot topic nowadays.In this paper,the problem of exponential synchronization for partially coupled stochastic neural networks with time delays is studied.First,a partially coupled stochastic neural network model with time delay is established.Then,according to the concept of synchronization,a controlled response system is constructed to obtain the error dynamics neural network.The stability of the error dynamics neural network is studied by using the Lyapunov stability theory to solve the problem of exponential synchronization of the drive response system.The main research results of this paper are as follows:First,in actual networks,network nodes are usually disturbed by some communication noise.In most cases,these noises are either indeterminate or random.However,in most cases,these noises may cause instability in the actual network.If these tiny,independent,random factors are superimposed,then the overall effect can be seen as normal distribution.According to the nature of these noise disturbances,it is found that Brownian motion can describe it properly.Therefore,a random neural network model with Gaussian white noise is established in this paper.Second,delays can be seen everywhere in real life,such as late trains,delays in the transmission of telephone signals,and even delays in the transmission of sounds in conversations.The influence of time lag refers to the system's current state at a certain moment in the past or in a certain historical period.Time lag phenomenon often occurs in the neural network,and it may lead to instability of the system,which results in the loss of human and financial resources.Therefore,the negative impact of time lag can not be ignored.In this paper,the neural network model with time delay is considered,and the neural network is indexed synchronously under the condition that the relevant conditions are satisfied,and the stability of the network is achieved.Third,in order to synchronize the state quantities in the neural network,information transmission occurs between the nodes.In general,nodes need to connect to form channels to communicate information to their corresponding level of information.At present,most documents consider that the nodes are completely connected or not connected at all.In an actual network,due to various interferences,only some channels can work normally.As a result,only some nodes are connected and some of the information is transmitted successfully.In this paper,considering the partial coupling of neural networks,and by using external synchronization,we can ignore the internal topology of neural networks to solve the synchronization problem,which has important practical significance.Fourth,the neural network itself cannot achieve synchronization well,so the network control problem has caused more and more research.In this paper,pulse control is set to solve the stability problem of the system.There are two main advantages of this control method: on one hand,pulse control can achieve control in discontinuous time;on the other hand,pinning control requires only a few key nodes to operate instead of all nodes.Considering these two advantages comprehensively,the impulse control can achieve effective control with high efficiency and low cost.Fifth,using the Lyapunov stability theory to obtain a stable error dynamics neural network,we can derive the exponential synchronization of partially coupled stochastic neural networks with time delays.Applying the theoretical research to real estate investment,discussing the synchronization between the capital-driven system of real estate investment and the target element response system of economic growth,the result of the synchronization between the two is to achieve a sustainable and coordinated development of real estate investment and economy.The parameters were set for numerical simulation.The feasibility of the proposed impulse control method was proved,and the validity of the model was proved.