Stability Of Two Kinds Of Neural Network Models In Quaternion-Valued

This paper is concerned with the lagrange exponential stability problem of BAM shunting inhibitory cellular neural networks and the global exponential stability of inertial neural networks in quaternion-valued.In the first question,when the activation function satisfies certain conditions,by combining the Lyapunov function approach and some inequalities techniques,different sufficient criteria including algebraic condition and the conditions based on the LMI are to ensure the stability of the system,meanwhile,different global exponential convergent ball are also estimated,in the end,the validity and disadvantages of these results are verified by an example.In the second question,applying ides of vector Lyapunov function inequality and Holandry differential inequality,it is deduced that the inertial neural network is globally exponential stability under the influence of impulse.In the end,the validity and rationality of the results are verified by examples.