Wavelet methods for time series analysis ebook

Wavelet methods for time series analysis Andrew T. Walden, Donald B. Percival
Publisher: Cambridge University Press

Название: Wavelets method for time series analysis Автор: Percival D. . No, but of course there are examples where weather and climate data time series both from observations and from climate models have been analyzed with wavelets. Secondly, this dissertation introduces wavelet methods for time series analysis. Topics in Combinatorial Optimization, Spring 2004. Time Series Analysis, Fall 2002. Topics in Brain and Cognitive Sciences Human Ethology, Spring 2001. The principle and algorithms of discrete wavelet transform (DWT) and maximal overlap discrete wavelet transform (MODWT) are introduced. Summary: Wavelet-based morphometry (WBM) is an alternative strategy to voxel-based morphometry (VBM) consisting in conducting the statistical analysis (i.e., univariate tests) in the wavelet domain. This method derives images of functional neural networks from singular-value decomposition of BOLD signal time series, and allows derivation of images when the analyzed BOLD signal is constrained to the scans occurring in peristimulus time, using all other scans as baseline. Издательство: Cambridge university press Год: 2006 Страниц: 611 Формат: djvu Размер: 16 Mb Язык: английский The analys. Mit civil mit foreign languages literatures. The OCW Finder Wavelets, Filter Banks and Applications, Spring 2003.