There exists a great deal of periodic non-stationary processes in natural,social and eco- nomical phenomenon.It is very important to realize the dynamic analysis and real-time forecast within a period.In this letter,a...There exists a great deal of periodic non-stationary processes in natural,social and eco- nomical phenomenon.It is very important to realize the dynamic analysis and real-time forecast within a period.In this letter,a wavelet-Kalman hybrid estimation and forecasting algorithm based on step-by-step filtering with the real-time and recursion property is put forward.It combines the advantages of Kalman filter and wavelet transform.Utilizing the information provided by multi- sensor effectively,this algorithm can realize not only real-time tracking and dynamic multi-step fore- casting within a period,but also the dynamic forecasting between periods,and it has a great value to the system decision-making.Simulation results show that this algorithm is valuable.展开更多
基金Supported by the National Natural Science Foundation of China (No.60434020,60572051)International Cooperative Project Foundation (0446650006)Ministry of Education Science Foundation (205092).
文摘There exists a great deal of periodic non-stationary processes in natural,social and eco- nomical phenomenon.It is very important to realize the dynamic analysis and real-time forecast within a period.In this letter,a wavelet-Kalman hybrid estimation and forecasting algorithm based on step-by-step filtering with the real-time and recursion property is put forward.It combines the advantages of Kalman filter and wavelet transform.Utilizing the information provided by multi- sensor effectively,this algorithm can realize not only real-time tracking and dynamic multi-step fore- casting within a period,but also the dynamic forecasting between periods,and it has a great value to the system decision-making.Simulation results show that this algorithm is valuable.
