论文部分内容阅读
文章对存在区间时变时滞的离散切换神经网络设计鲁棒非脆弱性广义H2滤波器.考虑滤波器存在参数摄动情况下仍能保证其执行的精确性,采用服从Bernoulli分布的随机变量描述滤波器增益变化的发生率,采用范数有界不确定性描述滤波器误差引起的不确定性.通过设计Lyapunov-Krasovskii泛函,得到保证滤波误差系统均方指数稳定的充分条件,使得系统在有外部干扰影响时确保其广义H2性能.最后,通过数值算例验证该滤波器设计算法的有效性.
In this paper, a robust and non-fragile generalized H2 filter is designed for discrete switched neural networks with time-varying delays in the interval. The accuracy of the proposed filter is guaranteed considering the existence of parameters perturbation, and the description of random variables subject to Bernoulli distribution By using the Lyapunov-Krasovskii functional, the sufficient conditions for ensuring the mean square exponential stability of the filter error system are obtained, which makes the system work well under the conditions of the filter uncertainties, The generalized H2 performance is guaranteed with external disturbances.Finally, numerical examples are given to verify the effectiveness of the proposed filter design algorithm.