Selection of Embedding Parameters for Nonlinear Models: Application to Physiological Time Series Data
The usual approach to nonlinear time series modeling consists of two steps: reconstruct the topological structure of the dynamics (with a time delay embedding), and perform some surface fitting to estimate the evolution operator. We show that the usual method of estimating time delay and embedding dimension is sub-optimal when one is concerned with modeling the dynamics. We introduce an algorithmic method for choosing the optimal embedding strategy and show that this provides improved modeling results for experimental time series of human infant respiratory effort and arrhythmic human electrocardiogram recordings.
Michael Small Chi K. Tse
Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong
国际会议
上海
英文
117
2003-11-09(万方平台首次上网日期,不代表论文的发表时间)