Intrinsic feature extraction in the COI of wavelet power spectra of climatic signals

摘要：

Since the wavelet power spectra are distorted at data boundaries (the cone of influence, COI), using traditional methods, one cannot judge whether there is a significant region in COI or not. In this paper, with the help of a first-order autoregressive (AR1) extension and using our simple and rigorous method, we can obtain realistic significant regions and intrinsic feature in the COI of wavelet power spectra. We verify our method using the 300 year record of ice extent in the Baltic Sea.

关键词： wavelet power spectrum AR1 extension feature extraction

作者: Zhihua Zhang John Moore

作者单位: College of Global Change and Earth System Science Beijing Normal University Beijing, China State Key Laboratory of Earth Surface Processes and Resource Ecology/College of Global Change and Ea

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 2380-2382

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）