Neural Processing Letters ( IF 3.1 ) Pub Date : 2021-01-18 , DOI: 10.1007/s11063-020-10422-5 Xiaohong Wang , Zhen Wang , Jianwei Xia , Qian Ma
This paper addresses the problem of quantized sampled-data control for CVNNs with time-varying delay under the assumption that only quantized measurements are transmitted to the controller. Based on the discrete-time Lyapunov stability theory, reciprocally convex approach, a sector bound approach, and some estimation techniques, a reduced conservative stabilization criterion is obtained to guarantee the exponential stabilization of the considered CVNNs. The desired quantized sampled-data controller is designed via converting the complex-valued linear matrix inequality into real-valued ones. The effectiveness of the derived criteria are shown via an illustrative simulation example.
中文翻译:
时滞复数值神经网络指数稳定的量化采样数据控制
在仅将量化测量值传输到控制器的假设下,本文解决了具有时变延迟的CVNN的量化采样数据控制问题。基于离散Lyapunov稳定性理论,往复凸方法,扇形界方法和一些估计技术,获得了简化的保守稳定准则,以保证所考虑的CVNN的指数稳定。通过将复数值线性矩阵不等式转换为实数值,设计所需的量化采样数据控制器。通过说明性的仿真示例显示了导出标准的有效性。