This paper presents a detail analysis on the Electrocardiogram (ECG) denoising approaches based on noise reduction algorithms in Empirical Mode Decomposition (EMD) and Discrete Wavelet Transform (DWT) domains. Compared to other denoising methods such as; filtering, independent and principle component analysis, neural networks, and adaptive filtering, EMD and wavelet domain denoising algorithms ...

New methods for compact image coding based on generalized wavelet decompositions have been introduced recently. Unlike in the classical wavelet decomposition scheme it is possible to use diier-ent scaling and wavelet functions at every scale by using non-stationary multiresolution analyses. In this work we introduce parallel algorithms (suitable for MIMD architectures) that excel the execution ...

Various results on constructing wavelets, multiwavelets and wavelet frames for periodic functions are reviewed. The orthonormal and Riesz bases as well as frames are constructed from sequences of subspaces called multiresolution analyses. These studies employ general frequency-based approaches facilitated by functions known as orthogonal splines and polyphase splines. While the focus is on the ...

Using wavelet analysis approach, the temporal variations of solar activity on time scales ranging from days to decades are examined from the daily time series of sunspot numbers. A hierarchy of changing complex periods is careful detected and related cycles compared with results from recent similar analyses. A general determination of the main Schwabe cycle length variations is also suggested o...

Abstract: In a power system, the analysis of transient signals is the theoretical basis of fault diagnosis and transient protection theory. Shannon wavelet entropy (SWE) and Shannon wavelet packet entropy (SWPE) are powerful mathematics tools for transient signal analysis. Combined with the recent achievements regarding SWE and SWPE, their applications are summarized in feature extraction of tr...

New methods for lossy image compression based on generalized wavelet decompositions have been introduced recently. Unlike in the classical wavelet decomposition scheme it is possible to use diierent scaling and wavelet functions at every scale by using non-stationary multiresolution analyses. This freedom in using diierent functions can be exploited for adaptive compression techniques. In this ...

The wavelet transform is a widely used time-frequency tool for signal processing. However, with some rare exceptions, its use in signal processing is limited to discrete-time critically sampled transforms, which are particular cases of subband coding. On the other hand, interest in continuous wavelet analyses has been repeatedly demonstrated in the literature. However, implementation challenges...

This paper examines wavelet analyses for detecting and characterizing printing defects. Positive wavelet features for this application include localized space-frequency properties for characterizing defects of limited spatial support (in contrast with the Fourier analysis, which has no spatial localization over the analysis region). In addition, the scale based analyses of wavelets mimic proper...