In this chapter we will survey methods for comparison and description of sampled movement data, with focus on techniques able to capture the characteristics of the temporal evolution of the signals under study. Functional data analysis, the cross wavelet transform and cross recurrence analysis will be introduced and applied to the analysis of speech movement data.

This paper proposes time-frequency analysis of EEG spectrum and wavelet analysis in EEG de-noising. In this paper, the basic idea is to use the characteristics of multi-scale multi-resolution, using four different thresholds to wipe off interference and noise after decomposition of the EEG signals. By analyzing the results, understanding the effects of four different methods, it comes to a conc...

Bernard Jones told you about multiresolution analysis in his wavelet lectures. This is a pretty well formalized and self-contained area of wavelet analysis. Multiscale methods form a wider and less well defined area of tools and approaches; the term is used, e.g., in numerical analysis, but the main range of multiscale methods are based on application of wavelets. In this this lecture I shall e...

Here we introduce our application of the wavelet analysis method to DNA sequences. In the signal processing field, Fourier transform is popular for analyzing wave data. However, although this method can process frequency information, it fails to handle locational data. In contrast, the wavelet method accommodates both locational and frequency information for wave analysis. The wavelet method is...

PURPOSE To investigate the proper usage of wavelet analysis in infantile nystagmus syndrome (INS) and determine its limitations and abilities. METHODS Data were analyzed from accurate eye-movement recordings of INS patients. Wavelet analysis was performed to examine the foveation characteristics, morphologic characteristics and time variation in different INS waveforms. Also compared were the...

Wavelet shrinkage is an effective nonparametric regression technique, especially when the underlying curve has irregular features such as spikes or discontinuities. The basic idea is simple: take the discrete wavelet transform (DWT) of data consisting of a signal corrupted by noise; shrink or remove the wavelet coefficients to remove the noise; and then invert the DWT to form an estimate of the...

F005. Hubbard, B. B. [1998] The world according to wavelets the story of a mathematical technique in the making. 2 Edition, A K Peters. Qian, S. [2002] Introduction to time-frequency and wavelet transforms.

Thanks to their capability to cover large areas, in all weather conditions, during the day as well as during the night, spaceborne Synthetic Aperture Radar (SAR) techniques constitute an extremely promising alternative to traditional surveillance methods. Nevertheless, in order to assure further usability of SAR images, specific data mining methods are still to be developed to provide an effici...

Yan Zhao 1,2,*, Zhimin Li 1 and Yonghui Nie 3 1 Department of Electrical Engineering, Harbin Institute of Technology, Harbin 150001, China; [email protected] 2 Department of Power Transmission and Transformation Technology College, Northeast Dianli University, Jilin 132012, China 3 Academic Administration Office, Northeast Dianli University, Jilin 132012, China; [email protected] * Corresp...