报告人：中山大学石杨博士
报告题目：Discrete time-variant problem solving via DTZNN model
报告时间：2018年3月16日10:00
报告地点：理工楼212
内容简介：
In this talk, a new discrete-time zeroing neural network model (termed DTZNN model) has been presented and investigated for solving discrete time-variant problem. Specifically, first of all, as a previous research, this talk will present continuous-time zeroing neural network model. Secondly, we will present the state-of-the-art technologies of discrete-time zeroing neural network model, such as 4-point new finite difference formula. Moreover, we will further discuss the real-world applications, such as robot manipulator control problem.
