We consider the use of wavelet transformations as a dimensionality reduction technique to permit efficient similarity search over high-dimensional time-series data. While numerous transformations have been proposed and studied, the only wavelet that has been shown to be effective for this application is the Haar wavelet. In this work, we observe that a large class of wavelet transformations (no...

Volterra integral equations arise in many problems pertaining to mathematical physics like heat conduction problems. Several numerical methods for approximating the solution of Volterra integral equations are known [1-10]. This paper is focused on the solution of Volterra integral equations of the second kind with weakly singular kernel via Haar function by taking advantage of the nice properti...

We propose a new “Haar-Fisz” technique for estimating the time-varying, piecewise constant local variance of a locally stationary Gaussian time series. We apply our technique to the estimation of the spectral structure in the Locally Stationary Wavelet model. Our method combines Haar wavelets and the variance stabilizing Fisz transform. The resulting estimator is mean-square consistent, rapidly...

In recent years, there has been greater attempt to find numerical solutions of differential equations using wavelet's methods. The following method is based on vector forms of Haar-wavelet functions. In this paper, we will introduce one dimensional Haar-wavelet functions and the Haar-wavelet operational matrices of the fractional order integration. Also the Haar-wavelet operational matrices of ...

We use Cramér-Chernoff type estimates in order to study the Calderón-Zygmund structure of kernels ? I ? D a ( ? ) ? x y , and their concentration about mean, where are subgaussian independent random variables { : } is wavelet basis dyadic intervals R . consider both, cases standard smooth wavelets case Haar wavelet.

In this paper we present certain results about the compression of images using wavelets. We concentrate on the simplest case of the Haar decomposition and compression in L. Further results about compression in L, p 6= 2 are mentioned. §

The collocation problem for noisy data with a piecewise constant noise variance is considered. An equivalence to the WIENERKOLMOGOROV equations in stationary collocation theory is constructed. A numerical solution based on HAAR wavelets is given.