In this paper, an automatic system is presented for word recognition using real Turkish word signals. This paper especially deals with combination of the feature extraction and classification from real Turkish word signals. A Discrete Wavelet Neural Network (DWNN) model is used, which consists of two layers: discrete wavelet layer and multi-layer perceptron. The discrete wavelet layer is used f...

An adaptive multilevel wavelet collocation method for solving multi-dimensional elliptic problems with localized structures is described. The method is based on multi-dimensional second generation wavelets, and is an extension of the dynamically adaptive second generation wavelet collocation method for evolution problems [Int. J. Comp. Fluid Dyn. 17 (2003) 151]. Wavelet decomposition is used fo...

Removing divergences in the negative moments of the multi-fractal partition function with the wavelet transformation ABSTRACT We present a promising technique which is capable of accessing the divergence free component of the partition function for the negative moments of the multi-fractal analysis of data using the wavelet transformation. It is based on implicitly bounding the local logarithmi...

The feature dimension and redundancy can reduce the face recognition speed and rate, the shading and light changing can heavily affect the face recognition effect. So the first key to face recognition is how to effectively extract face features because the face image contains a lot of redundant information. Multi-wavelet transform has symmetry, orthogonality, compact support and high vanishing ...

The information which is contained in the multi-spectral and SAR images have different characteristic. Multi-spectral images contain a great deal of spectral information, whereas SAR images contain rich texture information, such as buildings and road network. SAR and TM images fusion based on the wavelet transform ensure the fusion image showing more spatial detail, not only conserving the spec...

This paper presents an adaptive backstepping controller for a class of multi input multi output (MIMO) underactuated system, with uncertain dynamics, in its original nonsquare form. The proposed controller combines a wavelet based backstepping controller and a robust control term to obtain the desired tracking performance. Proposed scheme utilizes the concept of regularized inverse for effectiv...

Wavelet analysis as a recently data filtering method (or multi-scale decomposition) is particularly useful for describing signals with sharp spiky, discontinuous or fractal structure in financial markets. This study investigates the optimal several wavelet thresholding criteria or techniques to support the multi-signal decomposition methods of a daily Korean won / U.S. dollar currency market as...

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...