Lokális energiamódszer kicsi rendben gerjesztett Liénard-egyenletekre (Local energy method for little order forced equations)

Az x''+f(x) x'+g(x) = 0 alakú Liénard-típusú differenciálegyenlet központi szerepet játszik az üzleti ciklusok Káldor-Kalecki-féle [3,4] és Goodwin-féle [2] modelljeiben, sőt egy a munkanélküliség és vállalkozás-ösztönzések ciklikus változásait leíró újabb modellben [1] is. De ugyanez a nemlineáris egyenlettípus a gerjesztett ingák és elektromos rezgőkörök elméletét is felöleli [5]. Az ezzel kapcsolatos irodalom nagyrészt a határciklusok létezését vizsgálja (pl. [5]), pedig az alapvető stabilitási kérdések jóval áttekinthetőbb módon kezelhetők, s a kapott eredmények közvetve a határciklusok létezésének feltételeit is sokkal jobban be tudják határolni. Jelen dolgozatban az egyváltozós analízis hatékony nyelvezetével olyan egyszerűen megfogalmazható eredményekhez jutunk, amelyek képesek kitágítani az üzleti és más közgazdasági ciklusok modelljeinek kereteit, illetve pl. az [1]-beli modellhez újabb szemléltető speciális eseteket is nyerünk. ____ The Liénard type differential equation of the form x00 + f(x) ¢ x0 + g(x) = 0 has a central role in business cycle models by Káldor [3], Kalecki [4] and Goodwin [2], moreover in a new model describing the cyclical behavior of unemployment and entrepreneurship [1]. The same type of nonlinear equation explains the features of forced pendulums and electric circuits [5]. The related literature discusses mainly the existence of limit cycles, although the fundamental stability questions of this topic can be managed much more easily. The achieved results also outline the conditions for the existence of limit cycles. In this work, by the effective language of real valued analysis, we obtain easy-formulated results which may broaden the frames of economic and business cycle models, moreover we may gain new illustrative particular cases for e.g., [1].

Complex-valued b-spline neural networks for modelling and inverse of wiener systems

Communication signal processing applications often involve complex-valued (CV) functional representations for signals and systems. CV artificial neural networks have been studied theoretically and applied widely in nonlinear signal and data processing [1–11]. Note that most artificial neural networks cannot be automatically extended from the real-valued (RV) domain to the CV domain because the resulting model would in general violate Cauchy-Riemann conditions, and this means that the training algorithms become unusable. A number of analytic functions were introduced for the fully CV multilayer perceptrons (MLP) [4]. A fully CV radial basis function (RBF) nework was introduced in [8] for regression and classification applications. Alternatively, the problem can be avoided by using two RV artificial neural networks, one processing the real part and the other processing the imaginary part of the CV signal/system. A even more challenging problem is the inverse of a CV

Convolution roots and differentiability of isotropic positive definite functions on spheres

We prove that any isotropic positive definite function on the sphere can be written as the spherical self-convolution of an isotropic real-valued function. It is known that isotropic positive definite functions on d-dimensional Euclidean space admit a continuous derivative of order [(d − 1)/2]. We show that the same holds true for isotropic positive definite functions on spheres and prove that this result is optimal for all odd dimensions.

Theory of functions of a real variable.

Mode of access: Internet.

Density of Polynomials in the L^2 Space on the Real and the Imaginary Axes and in a Sobolev Space

2000 Mathematics Subject Classification: 41A10, 30E10, 41A65.

Discretization of complex-order algorithms for control applications

In this article we describe several methods for the discretization of the differintegral operator sa, where α = u + jv is a complex value. The concept of the conjugated-order differintegral is also introduced, which enables the use of complex-order differintegrals while still producing real-valued time responses and transfer functions. The performance of the resulting approximations is analysed in both the time and frequency domains. Several results are presented that demonstrate its utility in control system design.

Disposable immunosensor using a simple method for oriented antibody immobilization for label-free real-time detection of an oxidative stress biomarker implicated in cancer diseases

This work proposes a novel approach for a suitable orientation of antibodies (Ab) on an immunosensing platform, applied here to the determination of 8-hydroxy-2′-deoxyguanosine (8OHdG), a biomarker of oxidative stress that has been associated to chronic diseases, such as cancer. The anti-8OHdG was bound to an amine modified gold support through its Fc region after activation of its carboxylic functions. Non-oriented approaches of Ab binding to the platform were tested in parallel, in order to show that the presented methodology favored Ab/Ag affinity and immunodetection of the antigen. The immunosensor design was evaluated by quartz-crystal microbalance with dissipation, atomic force microscopy, electrochemical impedance spectroscopy (EIS) and square-wave voltammetry. EIS was also a suitable technique to follow the analytical behavior of the device against 8OHdG. The affinity binding between 8OHdG and the antibody immobilized in the gold modified platform increased the charge transfer resistance across the electrochemical set-up. The observed behavior was linear from 0.02 to 7.0 ng/mL of 8OHdG concentrations. The interference from glucose, urea and creatinine was found negligible. An attempt of application to synthetic samples was also successfully conducted. Overall, the presented approach enabled the production of suitably oriented Abs over a gold platform by means of a much simpler process than other oriented-Ab binding approaches described in the literature, as far as we know, and was successful in terms of analytical features and sample application.

Disposable immunosensor with simple antibody orientation for label-free real-time detection of a cancer biomarker

This work proposes a novel approach for a suitable orientation of antibodies (Ab) on an immunosensing platform, applied here to the determination of 8-hydroxy-2’-deoxyguanosine (8OHdG), a biomarker of oxidative stress that has been associated to chronic diseases, such as cancer. The Anti-8OHdG was bound to an amine modified gold support through its Fc region after activation of its carboxylic functions. Non-oriented approaches of Ab binding to the platform were tested in parallel, in order to show that the presented proposal favored Ab/Ag affinity. The immunosensor design was evaluated by Quartz-Crystal microbalance with Dissipation, Atomic Force Microscopy, Electrochemical Impedance Spectroscopy (EIS) and Square-Wave Voltammetry. EIS was also a suitable technique to follow the analytical behavior of the device against 8OHdG. The affinity binding between 8OHdG and the antibody immobilized in the gold modified platform increased the charged transfer resistance across the electrochemical sep-up. The observed behavior was linear from 0.02 to 7.0 ng/mL of 8OHdG concentrations. The interference from Glucose, Urea and Creatinine was found negligible. An attempt of application to synthetic samples was also successfully conducted. Overall, the presented approach enabled the production of suitably oriented Abs over a gold platform by means of a much simpler process than other oriented-Ab binding approaches described in the literature, as far as we know, and was successful in terms of analytical features and sample application.

The short and long-run determinants of the real exchange rate in Mexico

This paper explores the real exchange rate behavior in Mexico from 1960 until 2005. Since the empirical analysis reveals that the real exchange rate is not mean reverting, we propose that economic fundamental variables affect its evolution in the long-run. Therefore, based on equilibrium exchange rate paradigms, we propose a simple model of real exchange rate determination which includes the relative labor productivity, the real interest rates and the net foreign assets over a long period of time. Our analysis also considers the dynamic adjustment in response to shocks through impulse response functions derived from the multivariate VAR model.

Learning-Based Approach to Real Time Tracking and Analysis of Faces

This paper describes a trainable system capable of tracking faces and facialsfeatures like eyes and nostrils and estimating basic mouth features such as sdegrees of openness and smile in real time. In developing this system, we have addressed the twin issues of image representation and algorithms for learning. We have used the invariance properties of image representations based on Haar wavelets to robustly capture various facial features. Similarly, unlike previous approaches this system is entirely trained using examples and does not rely on a priori (hand-crafted) models of facial features based on optical flow or facial musculature. The system works in several stages that begin with face detection, followed by localization of facial features and estimation of mouth parameters. Each of these stages is formulated as a problem in supervised learning from examples. We apply the new and robust technique of support vector machines (SVM) for classification in the stage of skin segmentation, face detection and eye detection. Estimation of mouth parameters is modeled as a regression from a sparse subset of coefficients (basis functions) of an overcomplete dictionary of Haar wavelets.

A fast two-grid and finite section method for a class of integral equations on the real line with application to an acoustic scattering problem in the half-plane

We consider the numerical treatment of second kind integral equations on the real line of the form ∅(s) = ∫_(-∞)^(+∞)▒〖κ(s-t)z(t)ϕ(t)dt,s=R〗 (abbreviated ϕ= ψ+K_z ϕ) in which K ϵ L_1 (R), z ϵ L_∞ (R) and ψ ϵ BC(R), the space of bounded continuous functions on R, are assumed known and ϕ ϵ BC(R) is to be determined. We first derive sharp error estimates for the finite section approximation (reducing the range of integration to [-A, A]) via bounds on (1-K_z )^(-1)as an operator on spaces of weighted continuous functions. Numerical solution by a simple discrete collocation method on a uniform grid on R is then analysed: in the case when z is compactly supported this leads to a coefficient matrix which allows a rapid matrix-vector multiply via the FFT. To utilise this possibility we propose a modified two-grid iteration, a feature of which is that the coarse grid matrix is approximated by a banded matrix, and analyse convergence and computational cost. In cases where z is not compactly supported a combined finite section and two-grid algorithm can be applied and we extend the analysis to this case. As an application we consider acoustic scattering in the half-plane with a Robin or impedance boundary condition which we formulate as a boundary integral equation of the class studied. Our final result is that if z (related to the boundary impedance in the application) takes values in an appropriate compact subset Q of the complex plane, then the difference between ϕ(s)and its finite section approximation computed numerically using the iterative scheme proposed is ≤C_1 [kh log⁡〖(1⁄kh)+(1-Θ)^((-1)⁄2) (kA)^((-1)⁄2) 〗 ] in the interval [-ΘA,ΘA](Θ<1) for kh sufficiently small, where k is the wavenumber and h the grid spacing. Moreover this numerical approximation can be computed in ≤C_2 N log⁡N operations, where N = 2A/h is the number of degrees of freedom. The values of the constants C1 and C2 depend only on the set Q and not on the wavenumber k or the support of z.

On the solvability of second kind integral equations on the real line

This paper considers general second kind integral equations of the form(in operator form φ − kφ = ψ), where the functions k and ψ are assumed known, with ψ ∈ Y, the space of bounded continuous functions on R, and k such that the mapping s → k(s, · ), from R to L1(R), is bounded and continuous. The function φ ∈ Y is the solution to be determined. Conditions on a set W ⊂ BC(R, L1(R)) are obtained such that a generalised Fredholm alternative holds: If W satisfies these conditions and I − k is injective for all k ∈ W then I − k is also surjective for all k ∈ W and, moreover, the inverse operators (I − k) − 1 on Y are uniformly bounded for k ∈ W. The approximation of the kernel in the integral equation by a sequence (kn) converging in a weak sense to k is also considered and results on stability and convergence are obtained. These general theorems are used to establish results for two special classes of kernels: k(s, t) = κ(s − t)z(t) and k(s, t) = κ(s − t)λ(s − t, t), where κ ∈ L1(R), z ∈ L∞(R), and λ ∈ BC((R\{0}) × R). Kernels of both classes arise in problems of time harmonic wave scattering by unbounded surfaces. The general integral equation results are here applied to prove the existence of a solution for a boundary integral equation formulation of scattering by an infinite rough surface and to consider the stability and convergence of approximation of the rough surface problem by a sequence of diffraction grating problems of increasingly large period.

Measuring European real estate investment performance: A comparison of different approaches

The performance of real estate investment markets is difficult to monitor because the constituent assets are heterogeneous, are traded infrequently and do not trade through a central exchange in which prices can be observed. To address this, appraisal based indices have been developed that use the records of owners for whom buildings are regularly re-valued. These indices provide a practical solution to the measurement problem, but have been criticised for understating volatility and not capturing market turning points in a timely manner. This paper evaluates alternative ‘Transaction Linked Indices’ that are estimated using an extension of the hedonic method for index construction and with Investment Property Databank data. The two types of indices are compared over Q4 2001 to Q4 2012 in order to examine whether movements in these indices are consistent. The Transaction Linked Indices show stronger growth and sharper declines than their appraisal based counterparts over the course of the cycle in different European markets and they are typically two to four times more volatile. However, they have some limitations; for instance, only country level indicators can be published in many cases owing to low trading volumes in the period studied.

Exact Search Directions for Optimization of Linear and Nonlinear Models Based on Generalized Orthonormal Functions

A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

Spaces of compact operators on C(2(m) circle plus [0, alpha]) spaces

We classify up to isomorphism the spaces of compact operators K(E, F), where E and F are Banach spaces of all continuous functions defined on the compact spaces 2(m) circle plus [0, alpha], the topological sum of Cantor cubes 2(m) and the intervals of ordinal numbers [0, alpha]. More precisely, we prove that if 2(m) and aleph(gamma) are not real-valued measurable cardinals and n >= aleph(0) is not sequential cardinal, then for every ordinals xi, eta, lambda and mu with xi >= omega(1), eta >= omega(1), lambda = mu < omega or lambda, mu is an element of [omega(gamma), omega(gamma+1)[, the following statements are equivalent: (a) K(C(2(m) circle plus [0, lambda]), C(2(n) circle plus [0, xi])) and K(C(2(m) circle plus [0, mu]), C(2(n) circle plus [0, eta]) are isomorphic. (b) Either C([0, xi]) is isomorphic to C([0, eta] or C([0, xi]) is isomorphic to C([0, alpha p]) and C([0, eta]) is isomorphic to C([0,alpha q]) for some regular cardinal alpha and finite ordinals p not equal q. Thus, it is relatively consistent with ZFC that this result furnishes a complete isomorphic classification of these spaces of compact operators. (C) 2010 Elsevier Inc. All rights reserved.