We show that the empirical eigenvalue measure for sum of d independent Haar distributed n-dimensional unitary matrices, converge for n → ∞ to the Brown measure of the free sum of d Haar unitary operators. The same applies for independent Haar distributed n-dimensional orthogonal matrices. As a byproduct of our approach, we relax the requirement of uniformly bounded imaginary part of Stieltjes t...

In this paper, we present the estimation of Poisson intensity based on hypothesis testing in the wavelet domain for any dimensional data. The testing framework for wavelet-based Poisson intensity estimation was first introduced by Kolaczyk, where a thresholding estimator, which realizes the hypothesis testing, is derived for Haar wavelet coefficients. Here we propose for the same wavelet a new ...

In this paper we are proving that Sawyer type condition for boundedness work for individual Haar multipliers, as well as for the Haar shift and other “well localized” operators.

Most of the physical systems exhibit some degree of time-varying behavior. Physical phenomena exhibit time-varying behavior for a number of reasons. Some of the systems are inherently time-varying and can not effectively be modeled using time invariant models. This paper deals with the identification of time-varying systems using Haar basis functions. Basis functions approach involves expanding...

Contents Preface ix 1. Wavelet and frame transforms originated from continuous and discrete splines, Amir Z. Averbuch and Valery A. Zheludev 1 1.1. Introduction 1 1.2. Preliminaries 4 1.3. Prediction filters originated from splines 9 1.4. Biorthogonal wavelet transforms generated by filter banks with downsampling factor N = 2 (diadic transforms) 17 1.5. Application of spline-based wavelet trans...

The DDHFm package is designed to perform data-driven Haar-Fisz (DDHF) variance stabilization. The basic DDHF method itself is described in [4, 5]. The modifications to DDHF to make it work successfully for microarray (or indeed similar kinds of replicate data) are described in [10]. The basic idea of the Haar-Fisz transform is very simple. First, a Haar wavelet transform is applied to the data....

Wavelets are mathematical tools for hierarchically decomposing functions. Wavelet Transform has been proved to be a very useful tool for image processing in recent years. It allows a function which may be described in terms of a coarse overall shape, plus details that range from broad to narrow. The most distinctive feature of Haar Transform lies in the fact that it lends itself easily to simpl...

Abstract. In the paper, a new original procedure for the evaluation of discrete Haar spectra for separate fragments (blocks) of a digital image is proposed. The procedure explores specific properties of Haar wavelets, refers to the assumption that Haar spectrum of the whole image is known, and is much faster than direct evaluation of Haar spectral coefficients for the respective image blocks. I...