The wavelet transform-domain least-mean square (WTDLMS) algorithm uses the self-orthogonalizing technique to improve the convergence performance of LMS. In WTDLMS algorithm, the trade-off between the steady-state error and the convergence rate is obtained by the fixed step-size. In this paper, the WTDLMS adaptive algorithm with variable step-size (VSS) is established. The step-size in each subf...

The advent of distributed and agile sensing systems that collect data in multiple locations and through a variety of sensing modalities has brought about new and exciting challenges to the field of signal processing. Motivated by problems that arise in the development of these systems, the thesis makes contributions in three domains: (1) distributed optimization for inference in sensor networks...

The paper advocates and implements a new panel structure model to investigate the club convergence hypothesis. The model consists of a set of linear dynamic models that characterize the behavior of growth rates within each convergence club and a logistic regression that classifies these linear models. An EM algorithm is used to estimate the system by maximum likelihood and inference is conducte...

The aim of this paper is to improve the convergence rate of frame algorithm based on Richardson iteration and Chebyshev methods. Based on Richardson iteration method, we first square the existing convergence rate of frame algorithm which in turn the number of iterations would be bisected and increased speed of convergence is achieved. Afterward, by using Chebyshev polynomials, we improve this s...

in this paper, a numerical solution for a system of linear fredholm integro-differential equations by means of the sinc method is considered. this approximation reduces the system of integro-differential equations to an explicit system of algebraic equations. the exponential convergence rate $o(e^{-k sqrt{n}})$ of the method is proved. the analytical results are illustrated with numerical examp...

We consider a simple through-the-origin linear regression example introduced by Rousseeuw, van Aelst and Hubert (1999). It is shown that the conventional least squares and least absolute error estimators converge in distribution without normalization and consequently are inconsistent. A class of weighted median regression estimators, including the maximum depth estimator of Rousseeuw and Hubert...

We consider geometric words ω1 · · ·ωn with letters satisfying the restricted growth property ωk ≤ d + max{ω0, . . . , ωk−1}, where ω0 := 0 and d ≥ 1. For d = 1 these words are in 1-to-1 correspondence with set partitions and for this case we show that the number of left-to-right maxima (suitable centered) does not converge to a fixed limit law as n tends to infinity. This becomes wrong for d ≥...

The problem of Dynamic Job Shop (DJS) scheduling is one of the most complex problems of machine scheduling. This problem is one of NP-Hard problems for solving which numerous heuristic and metaheuristic methods have so far been presented. Genetic Algorithms (GA) are one of these methods which are successfully applied to these problems. In these approaches, of course, better quality of solutions...

In this paper we consider two closely related problems: estimation of eigenvalues and eigenfunctions of the covariance kernel of functional data based on (possibly) irregular measurements, and the problem of estimating the eigenvalues and eigenvectors of the covariance matrix for highdimensional Gaussian vectors. In [A geometric approach to maximum likelihood estimation of covariance kernel fro...

Abstract: This paper presents a synthesis on the mathematical work done on level crossings of stationary Gaussian processes, with some extensions. The main results [(factorial) moments, representation into the Wiener Chaos, asymptotic results, rate of convergence, local time and number of crossings] are described, as well as the different approaches [normal comparison method, Rice method, Stein...