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This paper is concerned with an age-structured model in population dynamics. We investigate the uniqueness of solution for this type of nonlinear reaction-diffusion problem when the source term depends on the density, indicating the presence of, for example, mortality and reaction processes. Our result shows that in a spatial environment, if two population densities obey the same evolution equation and possess the same terminal data of time and age, then their distributions must coincide therein. This work is in commemoration of the first death anniversary of V. A. K's father. V. A. K thanks Prof. Nguyen Huy Tuan for introducing him the ultraparabolic problem. The work of V.A.K. was supported by the Research Foundation-Flanders (FWO) under the project 'Approximations for forward and inverse reaction-diffusion problems related to cancer models'. Lesnic, D (reprint author), Univ Leeds, Dept Appl Math, Leeds, W Yorkshire, England. amt5ld@maths.leeds.ac.uk

The paper deals with the singularly perturbed quasilinear initial value problem exhibiting initial layer. First the nature of solution of differential problem before presenting method for its numerical solution is discussed. The numerical solution of the problem is performed with the use of a finite-fitted difference scheme on an appropriate piecewise uniform mesh (Shishkin-type mesh). An error analysis shows that the method is first-order convergent except for a logarithmic factor, in the discrete maximum norm, independently of the perturbation parameter. Finally, numerical results supporting the theory are presented. The paper deals with the singularly perturbed quasilinear initial value problem exhibiting initial layer. First the nature of solution of differential problem before presenting method for its numerical solution is discussed. The numerical solution of the problem is performed with the use of a finite-fitted difference scheme on an appropriate piecewise uniform mesh (Shishkin-type mesh). An error analysis shows that the method is first-order convergent except for a logarithmic factor, in the discrete maximum norm, independently of the perturbation parameter. Finally, numerical results supporting the theory are presented.

In this paper the relation between religion and income is investigated using a micro-dataset for the Netherlands. Religiosity is measured by religious membership and by participation. Instead of estimating separately a religion and an income equation, joint regression is preferred since this generally yields more efficient estimates. Following the single equation approach, both religious measures are found to decrease significantly income and income is found to affect negatively religion. However, these cross-effects get insignificant once the equations are simultaneously estimated. In contrast, the effects of socio-economic characteristics on religion and income hardly differ between both approaches.This discussion paper has resulted in a publication in Applied Economics.

It is well-known that the primal quadratic growth condition of the classical augmented Lagrangian around a local minimizer can be obtained under the second-order sufficient optimality condition. In this paper, we show that those conditions are indeed equivalent. Moreover, we prove that the primal quadratic growth condition of the sharp augmented Lagrangian around a local minimizer is in fact equivalent to the weak second-order sufficient optimality condition. In addition, we present some secondary results involving the sharp augmented Lagrangian. Fil: Fernández Ferreyra, Damián Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Centro de Investigación y Estudios de Matemática. Universidad Nacional de Córdoba. Centro de Investigación y Estudios de Matemática; Argentina. Universidad Nacional de Córdoba; Argentina

The present paper deals with new modification of Gamma operators preserving polynomials in Bohman-Korovkin sense and study their approximation properties: Voronovskaya type theorems, weighted approximation and rate of convergence are captured. The effectiveness of the newly modified operators according to classical ones are presented in certain senses as well. Numerical examples are also presented, highlighting the performance of the new constructions of Gamma operators in the context of one dimensional approximation. WOS:000547724400001 2-s2.0-85087771520

Nesovic, Emilija/0000-0003-3600-0486 WOS: 000376031600006 In Minkowski space-time, timelike generalized Mannheim curves are studied by Akyigit and et al in [1]. In that paper, the authors take the Mannheim mate alpha* of the timelike curve a as a timelike curve in Minkowski space-time E-1(4). In this statement, the plane spanned by {B-1*, B-2*} becomes a spacelike plane. Thus the other possible cases such as timelike and null for the plane spanned by {B-1*, B-2*} is not considered. In this paper, by taking consideration of all possible causal characters of the plane spanned by{B-1*, B-2*}, we give the necessary and sufficient conditions for timelike curves ME to be generalized timelike Mannheim curves in terms of their curvature functions. Also, the related examples are given.

EgeUn###, In this paper, we study sine-Gordon equation in order to obtain exact solitary wave solutions in the domain of fractional calculus. By using the definition of conformable fractional derivative, we obtain analytical solutions of time, space and time-space fractional sine-Gordon equations. We analyze graphically the effect of fractional order on evolution of the kink and antikink type solitons.

In the present paper the authors consider the $\mathcal{P}_{\nu,2}$-transform as a generalization of the Widder potential transform and the Glasser transform. The $\mathcal{P}_{\nu,2}$-transform is obtained as an iteration of the the $\mathcal{L}_{2}$-transform with itself. Many identities involving these transforms are given. By making use of these identities, a number of new Parseval-Goldstein type identities are obtained for these and many other well-known integral transforms. The identities proven in this paper are shown to give rise to useful corollaries for evaluating infinite integrals of special functions. Some examples are also given as illustration of the results presented here., Comment: 13 pages

In this paper, we investigate the use of a continuous algorithm for the no-idle permutation flowshop scheduling (NIPFS) problem with tardiness criterion. For this purpose, a differential evolution algorithm with variable parameter search (vpsDE) is developed to be compared to a well-known random key genetic algorithm (RKGA) from the literature. The motivation is due to the fact that a continuous DE can be very competitive for the problems where RKGAs are well suited. As an application area, we choose the NIPFS problem with the total tardiness criterion in which there is no literature on it to the best of our knowledge. The NIPFS problem is a variant of the well-known permutation flowshop (PFSP) scheduling problem where idle time is not allowed on machines. In other words, the start time of processing the first job on a given machine must be delayed in order to satisfy the no-idle constraint. The paper presents the following contributions. First of all, a continuous optimisation algorithm is used to solve ...

In survival analysis, the classical Koziol-Green model under random censorship is commonly used for informative censoring. We propose in this paper an extension of this model in which we derive a nonparametric estimator for the distribution function of a survival time under two types of informative censoring. For the first type of informative censoring, we assume that the censoring time depends on the survival time through the expression of their joint distribution by an Archimedean copula. For the second type of informative censoring, we assume that the marginal distribution of the censoring time is a function of the marginal distribution of the survival time where this function is found through a section of a known copula function on the observed lifetime and the censoring indicator. We prove in this paper the uniform consistency of the new estimator and show the weak convergence of the associated process. Afterwards, we give some finite sample simulation results and illustrate this estimator on a real-life data set. The authors gratefully acknowledge the financial support from the IAP research Network P6/03 of the Belgian Government (Belgian Science Policy). Furthermore, the authors would like to thank the associate editor and two anonymous referees for their comments which improved the first version of this paper.

WOS: 000456971300005, In this paper, a generalized difference-based estimator is introduced for the vector parameter beta in the partially linear model when the errors are correlated. A generalized difference-based Liu estimator is defined for the vector parameter beta. Under the linear stochastic constraint r = R beta + e, a new generalized difference-based weighted mixed Liu estimator is introduced. The performance of this estimator over the generalized difference-based weighted mixed estimator and the generalized difference-based Liu estimator in terms of the mean squared error matrix criterion is investigated. Then, a method to select the biasing parameter d and non-stochastic weight. is considered. The efficiency properties of the newestimator are illustrated by a simulation study. Finally, the performance of the new estimator is evaluated for a real data set., Semnan University Research [266/97/17577], The third author's research is supported by Semnan University Research [grant number 266/97/17577].

© 2018 Informa UK Limited, trading as Taylor & Francis Group. To estimate the central tendency or location of a sample of interval-valued data, a standard statistic is the interval-valued sample mean. Its strong sensitivity to outliers or data changes motivates the search for more robust alternatives. In this respect, a more robust location statistic is studied in this paper. This measure is inspired by the concept of spatial median and makes use of the versatile generalized Bertoluzza's metric between intervals, the so-called dθ distance. The problem of minimizing the mean dθ distance to the values the random interval takes, which defines the spatial-type dθ-median, is analysed. Existence and uniqueness of the sample version are shown. Furthermore, the robustness of this proposal is investigated by deriving its finite sample breakdown point. Finally, a real-life example from the Economics field illustrates the robustness of the sample dθ-median, and simulation studies show some comparisons with respect to the mean and several recently introduced robust location measures for interval-valued data. ispartof: STATISTICS vol:52 issue:3 pages:479-502 status: published

This is an Accepted Manuscript of an article published by Taylor & Francis in Applicable Analysis on 02/12/2016, available online: https://doi.org/10.1080/00036811.2016.1263838. The paper deals with jump generators with a convolution kernel. Assuming that the kernel decays either exponentially or polynomially, we prove a number of lower and upper bounds for the resolvent of such operators. In particular we focus on sharp estimates of the resolvent kernel for small values of the spectral parameter. We consider two applications of these results. First we obtain pointwise estimates for principal eigenfunction of jump generators perturbed by a compactly supported potential (so-called nonlocal Schrödinger operators). Then we consider the Cauchy problem for the corresponding inhomogeneous evolution equations and study the behaviourofitssolutions.

In this paper, we investigate estimation methods to deal with situations where random intercepts are associated to time-varying covariates in the context of linear mixed models. First, a review of previous ways to deal with this so-called endogeneity issue is presented, then a new method based on shared random effects is proposed. Simulation studies and an empirical example are utilized to assess the performance of our proposed method. It is shown that our new approach is more efficient than most competitors and is robust to the misspecification of the random-effects distributions. The authors advise no direct funding is associated with the research reported on this article.

Have you ever questioned why do we almost always use vector calculus and differential equations in electromagnetics? Are these the only tools at our disposal for studying and modelling electromagnetic problems? Well, the answer is no and this paper is about an alternative approach to model electromagnetic problems using algebraic topology. This approach has a few advantages compared to the familiar differential formulation-based methods in modelling electromagnetic and multiphysics problems. In differential formulation we need one of the several numerical methods like finite difference, finite element, method of moments and spectral methods to obtain approximate solution to the electromagnetic problem. In contrast, algebraic topology-based method leads directly to discrete formulation using global quantities. Furthermore, in the case of electromagnetics, all underlying global quantities are scalars. Hence, there is no need for vector calculus. In addition, we also avoid interpolating local vector field quantities as required in several numerical methods. Though algebraic topology offers powerful and elegant tools for solving various engineering problems, many applied physicists and engineers are not familiar with this subject. This is partly due to the fact that most publications on this topic burden us with complicated mathematical analysis filled with convoluted jargons. If one can introduce the key ideas of algebraic topology using familiar concepts, computational and applied physics, and engineering community can appreciate and benefit from its advantages over methods based on differential formulation. With this goal, we present the main ideas of algebraic topology applied to electromagnetics problems.

WOS: 000407961100004, In this paper, the non-linear Schrodinger (NLS) equation was solved by a meshless method based on the moving least-squares approximation. Single-soliton solution and interaction of two colliding solitons were studied to validate the accuracy of the proposed method. In calculations, different weight functions in which Gaussian and Wendland's compactly supported functions were used. For the single-soliton solution of NLS equation whose analytical solution was known L-2, L-infinity error norms and invariants were calculated for two test problems. The obtained results were compared with both each other and some earlier results. Stability analysis of difference equation was done by applying the proposed method for NLS equation.

In this paper, we investigate inextensible flows of curves according to alternative moving frame in Euclidean space 𝔼3. Using the Prenet frame of the given curve, we present partial differential equations. The concepts with the inextensible flows are analyzed by using alternative moving frame.

In the present paper, we shall give a characterization for weak/strong Adams-type boundedness of the fractional maximal operator on generalized Orlicz-Morrey spaces., Integral Transform. Spec. Funct. (to appear)

In this paper we study an n-dimensional generalization of time-fractional diffusion-wave equation, where the Laplacian operator is replaced by the ultra-hyperbolic operator and the time-fractional derivative is taken in the Hilfer sense. The analytical solution is obtained in terms of the Fox's H-function, for which the inverse Fourier transform of a Mittag–Leffler-type function that contains in its argument a positive-definite quadratic form is calculated. Fil: Dorrego, Gustavo. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas y Naturales y Agrimensura. Departamento de Matemática; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Made available in DSpace on 2018-11-27T04:40:24Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-02-11 In disease mapping, the overall goal is to study the incidence or mortality risk caused by a specific disease in a number of geographical regions. It is common to assume that the response variable follows a Poisson distribution, whose average rate can be explained by a group of covariates and a random effect. For this random effect, it is considered conditional autoregressive (CAR) models, which carry information about the neighbourhood relationship between the regions. The focus of this paper was to explore and compare some CAR models proposed in the literature. An application with epidemiological data was conducted to model the risk of death due to Crohn's Disease and Ulcerative Colitis in the State of SAo Paulo - Brazil. Finally, a simulation study was done to strengthen the results and assess the performance of the models in the presence of various levels of spatial dependence. Univ Estadual Paulista, Fac Ciencias & Tecnol, Presidente Prudente, SP, Brazil Univ Estadual Paulista, Fac Ciencias & Tecnol, Presidente Prudente, SP, Brazil

WOS: 000371347600006 In this paper, we investigate the boundedness of the Hilbert transform H in the local Morrey-Lorentz spaces [GRAPHICS] , [GRAPHICS] , [GRAPHICS] . We prove that the operator H is bounded in [GRAPHICS] under the condition [GRAPHICS] , [GRAPHICS] . In the limiting case [GRAPHICS] , [GRAPHICS] , we prove that the operator H is bounded from the space [GRAPHICS] to the weak local Morrey-Lorentz space [GRAPHICS] . Also we show that for the limiting case [GRAPHICS] , [GRAPHICS] , the modified Hilbert transform [GRAPHICS] is bounded from the space [GRAPHICS] to the bounded mean oscillation space. Science Development Foundation under Republic of AzerbaijanScience Development Foundation (SDF) - Azerbaijan [EIF-2013-9(15)-46/10/1]; Presidium Azerbaijan National Academy of ScienceAzerbaijan National Academy of Sciences (ANAS) The research of V.S. Guliyev was partially supported by the grant of Science Development Foundation under the President of the Republic of Azerbaijan, Grant EIF-2013-9(15)-46/10/1 and by the grant of Presidium Azerbaijan National Academy of Science 2015.

Kara, Emrah Evren/0000-0002-6398-4065; Ilkhan, Merve/0000-0002-0831-1474 WOS: 000382279100008 In this paper, we define new spaces as a generalization of the Fibonacci difference sequence spaces. Also, we establish some inclusion theorems related to these spaces and find the alpha-, beta-, gamma-duals. Lastly, we characterize some matrix classes on these spaces.

This paper investigates the robust stability problem for dynamical neural networks in the presence of time delays and norm-bounded parameter uncertainties with respect to the class of non-decreasing, non-linear activation functions. By employing the Lyapunov stability and homeomorphism mapping theorems together, a new delay-independent sufficient condition is obtained for the existence, uniqueness and global asymptotic stability of the equilibrium point for the delayed uncertain neural networks. The condition obtained for robust stability establishes a matrix-norm relationship between the network parameters of the neural system, which can be easily verified by using properties of the class of the positive definite matrices. Some constructive numerical examples are presented to show the applicability of the obtained result and its advantages over the previously published corresponding literature results. Publisher's Version

This paper compares the methods for variability extraction from a univariate time series in real time. The online scale estimation is achieved by applying a robust scale functional to a moving time window. Scale estimators based on the residuals of a preceding regression step are compared with regression-free and model-free techniques in a simulation study and in an application to a real time series. In the presence of level shifts or strong non-linear trends in the signal level, the model-free scale estimators perform especially well. However, the investigated regression-free and regression-based methods have higher breakdown points, they are applicable to data containing temporal correlations, and they are much more efficient.

In this paper a technique to obtain a first approximation for singular inverse Sturm-Liouville problems with a symmetrical potential is introduced. The singularity, as a result of unbounded domain (-infinity, infinity), is treated by considering numerically the asymptotic limit of the associated problem on a finite interval (-L, L). In spite of this treatment, the problem has still an ill-conditioned structure unlike the classical regular ones and needs regularization techniques. Direct computation of eigenvalues in iterative solution procedure is made by means of pseudospectral methods. A fairly detailed description of the numerical algorithm and its applications to specific examples are presented to illustrate the accuracy and convergence behaviour of the proposed approach. TUBITAK, the Scientific and Technical Research Council of TurkeyTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) This research was supported by a grant from TUBITAK, the Scientific and Technical Research Council of Turkey. WOS:000352953800005

The Fueter theorem states that regular (resp. monogenic) functions in quaternionic (resp. Clifford) analysis can be constructed from holomorphic functions in the complex plane, hereby using a combination of a formal substitution and the action of an appropriate power of the Laplace operator. In this paper we interpret this theorem on the level of representation theory, as an intertwining map between certain -modules.

In this paper we study a class of distributions related to the r.v. , for different distributions of . The problem is related to the hitting point of a randomly oriented ray and generalizes the Cauchy distribution in different directions. We show that the distribution of solves the Laplace equation of order , possesses even moments of order , and has bimodal structure when is uniform. We study also a number of distributional properties of functionals of , including those related to the arcsine law. Finally we study the same problem in the Poincare half-plane and this leads to the hyperbolic distribution of which the main properties are explored. In particular we study the distribution of hyperbolic functions of , the law of sums of i.i.d. r.v.'s and the distribution of the area of random hyperbolic right triangles.

In this paper, we study the asymptotic behaviour of weak solutions for the regularized Benard problem. We establish the global existence and uniqueness of weak solutions of this problem and give a proof for the existence of global attractor in the three-dimensional case for this system.

In this paper, a variant of nonlinear Galerkin method is proposed and analysed for equations of motions arising in a Kelvin-Voigt model of viscoelastic fluids in a bounded spatial domain in IRd (d = 2, 3). Some new a priori bounds are obtained for the exact solution when the forcing function is independent of time or belongs to L-infinity in time. As a consequence, existence of a global attractor is shown. For the spectral Galerkin scheme, existence of a unique discrete solution to the semidiscrete scheme is proved and again existence of a discrete global attractor is established. Further, optimal error estimate in L-infinity(L-2) and L-infinity(H-0(1))-norms are proved. Finally, a modified nonlinear Galerkin method is developed and optimal error bounds are derived. It is, further, shown that error estimates for both schemes are valid uniformly in time under uniqueness condition.

WOS: 000333943700007, In this paper, we first derive a weighted Montgomery identity on time scales and then establish weighted Ostrowski-type, Trapezoid-type, Gruss-type and Ostrowski-Gruss-like inequalities on time scales, respectively. These results not only provide a generalization of the known results, but also give some other interesting inequalities on time scales as special cases., Qing Lan Project of Jiangsu Province; National Natural Science Foundation of China [41174165]; Tianyuan Fund of Mathematics [11126289]; Teaching Research Project of NUIST [12JY052], This work was sponsored by Qing Lan Project of Jiangsu Province, and was supported by the National Natural Science Foundation of China (Grant No. 41174165), the Tianyuan Fund of Mathematics (Grant No. 11126289) and the Teaching Research Project of NUIST (Grant No. 12JY052).

In this paper we introduce a modified slash distribution obtained by modifying the usual slash distribution. This new distribution is based on the quotient of two independent random variables, whose distributions are the normal and the power of an exponential distribution of scale parameter equals to two, respectively. In this way, the result is a new distribution whose kurtosis values are greater when compared with that of the slash distribution. We study the density, some properties, moments, kurtosis and make inferences by the method of moments and maximum likelihood. We introduce a multivariate version of this new distribution. Moreover, we provide two illustrations with real data showing that the new distribution fits better the data than the ordinary slash distribution.

In this paper, we shall develop a novel family of bimodal univariate distributions (also allowing for unimodal shapes) and demonstrate its use utilizing the well-known and almost classical data set involving durations and waiting times of eruptions of the Old-Faithful geyser in Yellowstone park. Specifically, we shall analyze the Old-Faithful data set with 272 data points provided in Dekking et al. [3]. In the process, we develop a bivariate distribution using a copula technique and compare its fit to a mixture of bivariate normal distributions also fitted to the same bivariate data set. We believe the fit-analysis and comparison is primarily illustrative from an educational perspective for distribution theory modelers, since in the process a variety of statistical techniques are demonstrated. We do not claim one model as preferred over the other.

To achieve cost effectiveness and reliability in design, this paper presents a probabilistic multi-objective model for optimal design of composite channels that have a cross-sectional shape of horizontal bottom and parabolic sides. The multiple objectives of channel design include minimizing the cost of channel construction, maximizing the probability of the expected channel capacity being greater than the design flow and minimizing the overtopping probability. In this study, the principles of first-order uncertainty analysis are adopted for handling uncertainty in parameters of the problem. The optimization model is solved using the particle swarm optimization method and Pareto-optimal solutions are generated for various combinations of overtopping probability and exceedance probability of channel capacity. The results show that the presented approach has good potential for exploring different alternative designs of open channels under input parameter uncertainty.

A density function is generally not well defined in functional data context, but we can define a surrogate of a probability density, also called pseudo-density, when the small ball probability can be approximated by the product of two independent functions, one depending only on the centre of the ball. The aim of this paper is to study two kernel methods for estimating a surrogate probability density for functional data. We present asymptotic properties of these estimators: the convergence in probability and their rates. Simulations are given, including a functional version of smoother bootstrap selection of the parameters of the estimate. Fil: Ferraty, Frédéric. Universite Paul Sabatier. Institut de Mathematiques de Toulouse; Francia Fil: Kudraszow, Nadia Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Departamento de Matemáticas; Argentina Fil: Vieu, Philippe. Universite Paul Sabatier. Institut de Mathematiques de Toulouse; Francia

In recent years, high-order methods have shown to be very useful in many practical applications, in which nonlinear systems arise. In this case, a classical method of positional astronomy have been modified in order to hold a nonlinear system in its establishments (that in the classical method is reduced to a single equation). At this point, high-order methods have been introduced in order to estimate the solutions of this system and, then, determine the orbit of the celestial body. We also have implemented a user friendly application, which will allow us to make a numerical and graphical comparison of the different methods with reference orbits, or user defined orbits., The authors would like to thank the referees for their valuable comments and suggestions that have improved the content of the paper. This research was supported by Ministerio de Ciencia y Tecnologia MTM2010-18539.

In this paper, we propose a method to assess influence in skew-Birnbaum–Saunders regression models, which are an extension based on the skew-normal distribution of the usual Birnbaum–Saunders (BS) regression model. An interesting characteristic that the new regression model has is the capacity of predicting extreme percentiles, which is not possible with the BS model. In addition, since the observed likelihood function associated with the new regression model is more complex than that from the usual model, we facilitate the parameter estimation using a type-EM algorithm. Moreover, we employ influence diagnostic tools that considers this algorithm. Finally, a numerical illustration includes a brief simulation study and an analysis of real data in order to show the proposed methodology.

The telegraph process models a random motion with finite velocity and it is usually proposed as an alternative to diffusion models. The process describes the position of a particle moving on the real line, alternatively with constant velocity+v or−v. The changes of direction are governed by a homogeneous Poisson process with rate λ>0. In this paper, we consider a change-point estimation problem for the rate of the underlying Poisson process by means of the least-squares method under the hypothesis of discrete-time sampling. Consistency, rate of convergence and distributional results for the change-point estimator are obtained under both fixed and random sampling. An application to real data is presented.

In this paper, we discuss a Birnbaum–Saunders distribution with an unknown shift parameter and apply it to wind energy modeling. We describe structural aspects of this distribution including properties, moments, mode and hazard and shape analyses. We also discuss estimation, goodness of fit and diagnostic methods for this distribution. A computational implementation in R language of the obtained results is provided. Finally, we apply such results to two unpublished real wind speed data from Chile, which allows us to show the characteristics of this statistical distribution and to model wind energy flux.

In this paper we consider Sharpe's single-index model or Sharpe's model, by assuming that the returns obtained follow a multivariate t elliptical distribution. Also, given that the returns of the market are not observable, the statistical analysis was made in the context of an errors-in-variables model. In order to analyze the sensibility to possible outliers and/or atypical returns of the maximum likelihood estimators the local influence method [10] was implemented. The results are illustrated by using a set of shares of companies belonging to the Chilean Stock Market. The main conclusion is that the t model with small degrees of freedom is able to incorporate possible outliers and influential returns in the data.

The paper introduces a new notion of stability for internal autonomous system descriptions that is referred to as “strong stability” and characterizes the case of avoiding overshoots for all initial conditions within a given sphere. This is a stronger notion of stability compared to alternative definitions (asymptotic, Lyapunov), which allows the analysis and design of control systems described by natural coordinates to have no overshooting response for arbitrary initial conditions. For the case of LTI systems necessary and sufficient conditions for strong stability are established in terms of the negative definiteness of the symmetric part of the state matrix. The invariance of strong stability under orthogonal transformations is established and this enables the characterisation of the property in terms of the invariants of the Schur form of the state matrix. Some interesting relations between\ud strong stability and special forms of coordinate frames are examined and links between the skewness of the eigenframe and the violation of strong stability are derived. The characterisation of properties of strong stability given here provides the basis for the development of feedback theory for strong stabilisation.

In S.E. Trione and S. Molina, The n-dimensional Hankel transform and complex powers of Bessel operator, to appear in Integral Transforms and Spec. Funct. we study a version of the n-dimensional Hankel transform h μ for μ=(μ1, …, μ n )∈ℝ n and μ i ≥−1/2 for all i. In this paper, we extend the n-dimensional Hankel transform to arbitrary values of μ∈ℝ n . Moreover, we obtain some results for the inverse of this extension. Fil: Molina, Sandra. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Departamento de Matemática; Argentina Fil: Trione, Susana Elena. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderon; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina

In this paper, we study a version of the n-dimensional Hankel transform on certain spaces ℋμ which were studied in [Molina, S., 2003, A generalization of the spaces ℋμ and and the space of multipliers. Actas del VII Congreso Dr. Antonio Monteiro, pp. 49–56.]. Moreover, we introduce an n-dimensional generalization of Bessel operator and we have studied its properties in relation to the Hankel transform. Moreover, we study some application to the study of the fractional powers of Bessel operator on L2 (Rn+). Fil: Trione, Susana Elena. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Instituto Argentino de Matemática Alberto Calderon; Argentina

In this paper the problem of on-line identification and adaptive control of a Wiener type non-linear system is studied. First, a Wiener model is defined whose linear and non-linear parts are described using Laguerre and piecewise linear basis functions, respectively. Then, an adaptive identification algorithm for this model is presented. A local convergence analysis for the adaptive identification is performed. The model obtained is used to adapt the parameters of a controller designed for the specific structure of the model. The complete scheme is applied to a simulation of a pH neutralization reactor subject to several perturbations. The results show the improved behaviour of the proposed scheme compared with other approaches found in the literature. Fil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina Fil: Cousseau, Juan Edmundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina Fil: Werner, Stefan. University of Helsinki; Finlandia Fil: Laakso, T.. University of Helsinki; Finlandia

This paper deals with the preconditioning of truncated Newton methods for the solution of large scale nonlinear unconstrained optimization problems. We focus on preconditioners which can be naturally embedded in the framework of truncated Newton methods, i.e. which can be built without storing the Hessian matrix of the function to be minimized, but only based upon information on the Hessian obtained by the product of the Hessian matrix times a vector. In particular we propose a diagonal preconditioning which enjoys this feature and which enables us to examine the effect of diagonal scaling on truncated Newton methods. In fact, this new preconditioner carries out a scaling strategy and it is based on the concept of equilibration of the data in linear systems of equations. An extensive numerical testing has been performed showing that the diagonal preconditioning strategy proposed is very effective. In fact, on most problems considered, the resulting diagonal preconditioned truncated Newton method performs ...

Intuitionistic fuzzy sets are extensions of fuzzy sets. Their elements have two degrees – a degree of membership and a degree of non-membership so that their sum is smaller or equal to 1. Intuitionistic fuzzy interpretations of the processes of multi-person and of multi-measurement tool multi-criteria decision makings are discussed in this paper.

A Wiener system is a system which can be modelled as a linear dynamic followed by a static gain. The goal of this paper is to develop a robust H ∞ compensator for controlling an SISO Wiener system. The controller also takes the form of a Wiener model. The design approach consists of the approximation of the non-linear gain using a piecewise linear (PWL) function and in using a linear controller for each sector obtained from this approximation. Therefore, the general controller structure can be stated as a linear dynamic compensator in series with a PWL static gain. As an illustrative case, a neutralization pH reaction between a strong acid and a strong base in the presence of a buffer agent is dealt with. Computer simulations are developed for showing the performance of the proposed controller. Fil: Biagiola, Silvina Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentina Fil: Agamennoni, Osvaldo Enrique. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina Fil: Figueroa, Jose Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages". Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras. Instituto de Investigaciones en Ingeniería Eléctrica "Alfredo Desages"; Argentina

The linear mixed-effects model (Verbeke and Molenberghs, 2000) has become a standard tool for the analysis of continuous hierarchical data such as, for example, repeated measures or data from meta-analyses. However, in certain situations the model does pose insurmountable computational problems. Precisely this has been the experience of Buyse et al. (2000a) who proposed an estimation- and prediction-based approach for evaluating surrogate endpoints. Their approach requires fitting linear mixed models to data from several clinical trials. In doing so, these authors built on the earlier, single-trial based, work by Prentice (1989), Freedman et al. (1992), and Buyse and Molenberghs (1998). While Buyse et al. (2000a) claim their approach has a number of advantages over the classical single-trial methods, a solution needs to be found for the computational complexity of the corresponding linear mixed model. In this paper, we propose and study a number of possible simplifications. This is done by means of a simulation study and by applying the various strategies to data from three clinical studies: Pharmacological Therapy for Macular Degeneration Study Group (1977), Ovarian Cancer Meta-analysis Project (1991) and Corfu-A Study Group (1995). The first, second, fourth, and fifth authors wish to thank "Bijzonder Onderzoeksfonds" of the Limburgs Universitair Centrum. We acknowledge support from Interuniversity Attraction Poles Programme P5=24-Belgian State-Federal Office for Scientific, Technical and Cultural Affairs.

WOS: 000176035700009 In literature, it has been reported that the convergence of some preconditioned stationary iterative methods using certain type upper triangular matrices as preconditioners are faster than the basic iterative methods. In this paper, a new preconditioned iterative method for the numerical solution of linear systems has been introduced, and the convergence analysis of the proposed method and an existing one have been done. Some numerical examples have also been given, which show the effectiveness of both of the methods.

Line-of-sight communication on topographic surfaces has relevance for several applications of Geographical Information Systems. In this paper, we study the problem of linking a set of transceiver stations in a visibility-connected communication network, by placing a minimum number of relays on the terrain surface. The problem is studied in the framework of a discrete visibility model, where the mutual visibility of a finite set of sites on the terrain is represented through a graph, called the visibility graph. While in the special case of only two transceivers an optimal solution can be found in polynomial time, by computing a minimum path on the visibility graph, the general problem is equivalent to a Steiner problem on the visibility graph, and, thus, it is untractable in practice. In the latter case, we propose a practical approximate solution based on a Steiner heuristic. For both the special and the general case, we propose both a static and a dynamic algorithm that allow computation of a s...

The first step in any system identification procedure is the collection of data and its preliminary analysis. This step is generally neglected in the literature because in this step the maximum amount of human judgement, experience and decision-making is needed. In this paper Zadeh's fuzzy set theory is used to systematize this preliminary analysis of data. A fuzzy measure termed the ‘degree of difficulty’ (DOD) is derived, which quantifies in a fuzzy manner the difficulty and complexity involved in a system identification problem. The computation of DOD is based on the membership functions developed for nine fuzzy sets defined using nine characterizing properties of systems.