Fuzzy Control and its Applications in QCM Sensor System
Research in the field of neural networks has made significant progress, that progress has attracted a lot of attention and support of the people more money on. Now more and more academic and commercial research is carried out on neural networks, such as chip-based neural networks are developed and applied, and produces a number of complex issues, and treats these problems solved. Obviously, now just a transition period of neural networks. Neural network results from the ability of complex data extraction can be used to extract or detect those patterns for humans or other computer technology is too complex hard to notice a trend. A class of design problems H∞ fuzzy neural network controller. By using Lyapunov-Krasovskii functional theory and judgment theorem to derive a stable process introduces several additional matrices, got some time delay depends on the H∞progressive. Finally, a numerical example is given to demonstrate the effectiveness and feasibility of the simulation we give H∞controller.
Neural Networks Pattern Recognition Numerical Analysis
CHEN Haixia
Tonghua Teachers College, China
国际会议
重庆
英文
699-702
2015-12-18(万方平台首次上网日期,不代表论文的发表时间)