In this paper, We use the wavelet bases of Hermite cubic splines to solve the second kind integral equations xCi) -11 K(t,s)x(s)ds = y(t), t E [0,1]. A pair of wavelets are constructed on the basis of Hermite cubic spline~: This wavelets are in C1 and supported on [0,2]. Moreover, one wavelet is symmetric, and the other is anti-symmetric. This spline wavelets are then adapted to the interval [0...

We encounter a wide range of sounds everyday which are harmonic, transient or a mixture of both. A number of models have been developed in recent years to synthesise harmonic sounds but these models do not perform effectively on transient sounds because of the sharp attack and decay part of the transient sounds. This paper presents a new technique for analysis-based synthesis of transient sound...

This paper addresses the analysis, modelling and simulation of measured full-scale wind pressure and velocity data. The records exhibit both non-Gaussian and nonstationary features, and are ideal for the application of a number of contemporary methods for handling the types of problems associated with these characteristics. Modelling the probability density function (PDF) of non-Gaussian pressu...

This thesis describes a set of tools for manipulating sampled signals using wavelet transforms, and outlines potential musical applications of this library. Wavelets improve on existing time frequency methods by representing signals as a sum of a single wavelet basis function at different positions and scales. A wavelet representation can be used to synthesize or transform sounds in a variety o...

This paper proposes a new method for load forecasting—the wavelet neural network model for daily load forecasting. The neural call function is basis of nonlinear wavelets. A wavelet network is composed by the wavelet basis function. The global optimum solution is got. We overcome the intrinsic defects of a artificial neural network that its learning speed is slow, its network structure is diffi...

We present a construction of a wavelet-type orthonormal basis for the space of radial L-functions in R via the concept of a radial multiresolution analysis. The elements of the basis are obtained from a single radial wavelet by usual dilations and generalized translations. Hereby the generalized translation reveals the group convolution of radial functions in R. We provide a simple way to const...

We construct a wavelet basis on the unit interval with respect to which both the (infinite) mass and stiffness matrix corresponding to the one-dimensional Laplacian are (truly) sparse and boundedly invertible. As a consequence, the (infinite) stiffness matrix corresponding to the Laplacian on the n-dimensional unit box with respect to the n-fold tensor product wavelet basis is also sparse and b...

In an effort to provide a more efficient representation of the acoustical speech signal in the pre-classification stage of a speech recognition system, we consider the application of the Best-Basis Algorithm of Coifman and Wickerhauser. This combines the advantages of using a smooth, compactly-supported wavelet basis with an adaptive time-scale analysis dependent on the problem at hand. We star...

This paper briefly describes the basic principle of wavelet packet analysis, and on this basis introduces the general principle of wavelet packet transformation for signal den-noising. The dynamic EEG data under +Gz acceleration is made a de-noising treatment by using wavelet packet transformation, and the de-noising effects with different thresholds are made a comparison. The study verifies th...

Image compression methods that use wavelet transforms have been successful in providing high rates of compression while maintaining good image quality. Even superior to these wavelet techniques are methods based on wavelet packet decompositions. When processing satellite data the amount of data suggests to use a parallel approach. Wavelet packet decomposition with best basis selection is implem...