研究具有区间时变分布时滞和不确定转移率的Markov跳变区间时变时滞神经网络的稳定性问题.通过充分考虑转移概率的性质和不确定区域的特性,用一个有效的技术代替传统的Young’s不等式来约束转移率中的不确定项.同时,利用增广的李雅普诺夫泛函和具有较小保守性的辅助函数积分不等式,给出新的时滞依赖的稳定条件.仿真结果验证了所提出方法的有效性. This paper studies the stability of time-varying delay neural networks with Markov transitions with time-varying distributed delays and uncertainties. By considering the properties of transition probabilities and the properties of uncertain regions, an effective technique is used to replace the traditional Young’s inequality is used to constrain the uncertainties in the transfer rate.At the same time, a new delay-dependent stability condition is given by using augmented Lyapunov functional and the conservative inequality of auxiliary functions.In the simulation results, The effectiveness of the proposed method.