A novel second-order DFP-based Volterra filter and its applications to chaotic time series prediction
A novel adaptive second-order Volterra filter based on Davidon-Fletcher-Powell (DFPSOVF) technique has been proposed. Recursive update formula of the inverse estimate of auto-correlation matrix in the DFPSOVF filter is presented. In order to avoid some problems caused by using LMS, NLMS or RLS algorithms, a variable convergence factor based on a posteriori error assumption, which can change with input signal changes in real time, is employed. Simulations, which apply the DFPSOVF filter to single step predictions for R鰏sler chaotic series and compare its results with those using LMS and NLMS algorithms to SOVF filter, respectively, illustrate that the proposed filter can always guarantee its stability and convergence and there haven抰 divergence problems caused by selecting inappropriate parameters with LMS and NLMS algorithms.
Volterra filter Davidon-Fletcher-Powell chaotic time series prediction variable convergence factor
ZHANG Yumei BAI Shulin CHEN Ping QU Shiru
Department of Automatic Control, Northwestern Polytechnical University, Xi’an 710072 School of Compu Xi’an Electronic Engineering Research Institute, Xi’an 710100 School of Electronics and Information, School of Computer Science, Shaanxi Normal University, Xi’an 710062 Department of Automatic Control, Northwestern Polytechnical University, Xi’an 710072
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
1036-1039
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）