The aim of this study is to evaluate a machine-learning method in which symbolic representations of folk songs are segmented and classified into tune families with Haar-wavelet filtering. The method is compared with previously proposed Gestaltbased method. Melodies are represented as discrete symbolic pitch-time signals. We apply the continuous wavelet transform (CWT) with the Haar wavelet at s...

In this paper, Haar wavelet-based neural network is described for the identification and control of discrete-time nonlinear dynamical systems. Wavelets are suited to depict functions with local nonlinearities and fast variations because of their intrinsic properties of finite support and self-similarity. Due to the orthonormal properties of Haar wavelet functions, wavelet neural networks result...

Previously, the use of non-separable wavelets in image processing has been hindered by the lack of a fast algorithm to perform a non-separable wavelet transform. We present two such algorithms in this paper. The rst algorithm implements a periodic wavelet transform for any valid wavelet lter sequence and dilation matrices satisfying a trace condition. We discuss some of the complicating issues ...

The goal of Iris recognition is to recognize human identity through the textural characteristics of one’s Iris muscular patterns. Iris recognition has been acknowledged as one of the most accurate biometric modalities because of its high recognition rate. Here performance comparison among various proposed techniques of Iris Recognition using the fractional coefficients of transformed Iris image...

Asymptotic expansions of the wavelet transform for large and small values of the translation parameter b are obtained using asymptotic expansions of the Fourier transforms of the function and the wavelet. Asymptotic expansions of Mexican hat wavelet transform, Morlet wavelet transform, and Haar wavelet transform are obtained as special cases. Asymptotic expansion of the wavelet transform has al...

Accurate groundwater level modeling and forecasting contribute to civil projects, land use, citys planning and water resources management. Combined Wavelet-Artificial Neural Network (WANN) model has been widely used in recent years to forecast hydrological and hydrogeological phenomena. This study investigates the sensitivity of the pre-processing to the wavelet type and decomposition level in ...

This paper proposes a modified simple but efficient calculation schema for 2D-Haar wavelet transformation in image compression. The proposed work is aimed at developing computationally efficient and effective algorithms for lossy image compression using wavelet techniques. The work is particularly targeted towards wavelet image compression using Haar Transformation with an idea to minimize the ...

Soft wavelet shrinkage, total variation (TV) diffusion, TV regularization, and a dynamical system called SIDEs are four useful techniques for discontinuity preserving denoising of signals and images. In this paper we investigate under which circumstances these methods are equivalent in the one-dimensional case. First, we prove that Haar wavelet shrinkage on a single scale is equivalent to a sin...

The classical Haar wavelet system of L2(R) is commonly considered to be very local in space. We introduce and study in this paper piecewise-constant framelets (PCF) that include the Haar system as a special case. We show that any bi-framelet pair consisting of PCFs provides the same Besov space characterizations as the Haar system. In particular, it has Jackson-type performance sJ = 1 and Berns...