报告题目：Gegenbauer processes and energy informatics
报 告 人：YangQuan Chen教授，美国加州大学
Gegenbauer polynomial has a generating function of a real power of a quadratic polynomial. When this quadratic polynomial is the z-transfer function of a second order IIR or FIR, raising this whole z-transfer function to the power of a real number, we will get an irrational z-transfer function whose output is called the Gegenbauer process driven by white noise. It turns out that, Gegenbauer process can exhibit both long range dependence (or long memory) and seasonality. This is particularly attractive in modeling time series in energy informatics. In this seminar, we will introduce k-factor Gegenbauer ARMA and its applications in time series modeling and prediction in energy informatics.
YangQuan Chen’s research interests include mechatronics for sustainability, cognitive process control, small multi-UAV based cooperative multi-spectral “personal remote sensing”, applied fractional calculus in controls, etc.
He now serves as Topic Editor-in-Chief of International Journal of Advanced Robotic Systems (Field Robotics), Section AE (Remote Sensors) for Sensors, Senior Editor for International Journal of Intelligent Robotic Systems, Topical AE for Nonlinear Dynamics (18-) and AE for IFAC Mechatronics, Intelligent Service Robotics, Energy Sources (Part A) (18-) and Fractional Calculus and Applied Analysis. He is a member of IEEE, ASME, AIAA, ASPRS, AUVSI and AMA.