Extracting clean fetal electrocardiogram (ECG) signals is very important in fetal monitoring. In this paper, we proposed a new method for fetal ECG extraction based on wavelet analysis, the least mean square (LMS) adaptive filtering algorithm, and the spatially selective noise filtration (SSNF) algorithm. First, abdominal signals and thoracic signals were processed by stationary wavelet transfo...

In this paper we will introduce a method of analyzing images, a criterium to differentiate between images, a compression method of medical images in digital form based on the classification of the image bit plane and finally an algorithm for adaptive image compression. The analysis of the image content is based on a valiation of the relative number and absolute values of the wavelet coefficient...

This paper presents an intelligent fault detection based on adaptive continuous wavelet transform of broken rotor bars for Induction Motor (IM). Broken rotor bars, bearing decay, eccentricity, as motor faults appears as different frequencies in the stator current signals. The stator current and speed signals at deferent operation conditions obtained from the winding function are analysed throug...

We develop three novel wavelet domain denoising methods for subband-adaptive, spatiallyadaptive and multivalued image denoising. The core of our approach is estimation of the probability that a given coefficient contains a significant noise-free component, which we call “signal of interest”. In this respect we analyze cases where the probability of signal presence is (i) fixed per subband, (ii)...

The recently developed essentially fourth-order or higher low dissipative shock-capturing scheme of Yee, Sandham and Djomehri (1999) aimed at minimizing numerical dissipations for high speed compressible viscous ows containing shocks, shears and turbulence. To detect non smooth behavior and control the amount of numerical dissipation to be added, Yee et al. employed an arti cial compression met...

Wavelet based image denoising methods have attracted extensive interests over the last decade. Donoho et. al. [3] first suggested to remove/suppress noise by thresholding of wavelet coefficients. The underlying assumption is simple and intuitive: a wavelet coefficient is treated as noise and set to zero if it is below a preset threshold. Otherwise, the coefficient is kept or slightly modified. ...

Wavelet based image denoising methods have attracted extensive interests over the last decade. Donoho et. al. [3] first suggested to remove/suppress noise by thresholding of wavelet coefficients. The underlying assumption is simple and intuitive: a wavelet coefficient is treated as noise and set to zero if it is below a preset threshold. Otherwise, the coefficient is kept or slightly modified. ...

In this paper a new method for adaptive synthesis of a smooth orthogonal wavelet, using fast neural network and genetic algorithm, is introduced. Orthogonal lattice structure is presented. A new method of supervised training of fast neural network is introduced to synthesize a wavelet with desired energy distribution between output signals from low–pass and high–pass filters on subsequent level...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

An adaptive multilevel wavelet solver for elliptic equations on an optimal spherical geodesic grid is developed. The method is based on second-generation spherical wavelets on almost uniform optimal spherical geodesic grids. It is an extension of the adaptive multilevel wavelet solver [O. V. Vasilyev and N. K.-R. Kevlahan, J. Comput. Phys., 206 (2005), pp. 412–431] to curved manifolds. Wavelet ...