On the relationship between the Method of Least Squares and Gram-Schmidt orthogonalization

The method of Least Squares is due to Carl Friedrich Gauss. The Gram-Schmidt orthogonalization method is of much younger date. A method for solving Least Squares Problems is developed which automatically results in the appearance of the Gram-Schmidt orthogonalizers. Given these orthogonalizers an induction-proof is available for solving Least Squares Problems.

Identification of linear systems in the presence of piecewise polynomial disturbances

The paper proposes a method of performing system identification of a linear system in the presence of bounded disturbances. The disturbances may be piecewise parabolic or periodic functions. The method is demonstrated effectively on two example systems with a range of disturbances.

Genetic Algorithm for the Determination of Linear Viscoelastic Relaxation Spectrum from Experimental Data

Conventional procedures employed in the modeling of viscoelastic properties of polymer rely on the determination of the polymer`s discrete relaxation spectrum from experimentally obtained data. In the past decades, several analytical regression techniques have been proposed to determine an explicit equation which describes the measured spectra. With a diverse approach, the procedure herein introduced constitutes a simulation-based computational optimization technique based on non-deterministic search method arisen from the field of evolutionary computation. Instead of comparing numerical results, this purpose of this paper is to highlight some Subtle differences between both strategies and focus on what properties of the exploited technique emerge as new possibilities for the field, In oder to illustrate this, essayed cases show how the employed technique can outperform conventional approaches in terms of fitting quality. Moreover, in some instances, it produces equivalent results With much fewer fitting parameters, which is convenient for computational simulation applications. I-lie problem formulation and the rationale of the highlighted method are herein discussed and constitute the main intended contribution. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 113: 122-135, 2009

Signal-flow graphs: Direct method of reduction and MATLAB implementation

Block diagrams and signal-flow graphs are used to represent and to obtain the transfer function of interconnected systems. The reduction of signal-flow graphs is considered simpler than the reduction of block diagrams for systems with complex interrelationships. Signal-flow graphs reduction can be made without graphic manipulations of diagrams, and it is attractive for a computational implementation. In this paper the authors propose a computational method for direct reduction of signal-flow graphs. This method uses results presented in this paper about the calculation of literal determinants without symbolic mathematics tools. The Cramer's rule is applied for the solution of a set of linear equations, A program in MATLAB language for reduction of signal-flow graphs with the proposed method is presented.

Determination of the photoinduced birefringence and of the refractive index by Brewster method of epoxy resin doped with CdS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An extension of the linear delta expansion to superspace

We introduce and discuss the method of linear delta expansion for the calculation of effective potentials in superspace, by adopting the improved version of the super-Feynman rules. Calculations are carried out up to two loops and an expression for the optimized Kahler potential in the Wess-Zumino model is worked out.

LMI-based digital redesign of linear time-invariant systems with state-derivative feedback

A simple method for designing a digital state-derivative feedback gain and a feedforward gain such that the control law is equivalent to a known and adequate state feedback and feedforward control law of a digital redesigned system is presented. It is assumed that the plant is a linear controllable, time-invariant, Single-Input (SI) or Multiple-Input (MI) system. This procedure allows the use of well-known continuous-time state feedback design methods to directly design discrete-time state-derivative feedback control systems. The state-derivative feedback can be useful, for instance, in the vibration control of mechanical systems, where the main sensors are accelerometers. One example considering the digital redesign with state-derivative feedback of a helicopter illustrates the proposed method. © 2009 IEEE.

On switched control design of linear time-invariant systems with polytopic uncertainties

This paper proposes a new switched control design method for some classes of linear time-invariant systems with polytopic uncertainties. This method uses a quadratic Lyapunov function to design the feedback controller gains based on linear matrix inequalities (LMIs). The controller gain is chosen by a switching law that returns the smallest value of the time derivative of the Lyapunov function. The proposed methodology offers less conservative alternative than the well-known controller for uncertain systems with only one state feedback gain. The control design of a magnetic levitator illustrates the procedure. © 2013 Wallysonn A. de Souza et al.

A critical analysis of the ubiquity of linear local-regional richness relationships

Synthesis Despite theoretical criticisms, the ubiquity of linear relationships between local and regional species richness has long been used to justify it as a valid framework to conclude that local communities are not saturated with species. However, we reanalyzed published studies with a new unbiased method and found no prevalence of linear relationships and more than 40% of misclassifications, including textbook examples. We thus conclude that the prevailing argument in favor of associating a valid ecological interpretation to local-regional species richness plots, its ubiquity, is not sustained, and that ecologists could use for instance metacommunity theory to make inference on the strength of local and regional processes. Identifying the relative importance of regional and local processes to local species diversity is a central issue to many questions in basic and applied ecology. One widely-used method is to plot local species richness against its regional richness to infer whether regional or local processes determine local diversity. However, this method increases the tendency to find regional prevalence as suggested by a recent simulation. We reanalyzed studies in the literature with an unbiased method and found no prevalence of either regional or local processes. In addition, almost 40% of the studies and 50% of the ecology textbook examples using the traditional method were misclassified. Our findings reinforce the need of alternative, novel tools identified by for instance metacommunity theory to go beyond the studies of local-regional relationships in the ecological literature that focus on the interdependence of regional and local processes.© 2013 The Authors. Oikos © 2013 Nordic Society Oikos.

Bayesian Analysis of Linear Inverse Problems with Applications in Economics and Finance

In my PhD thesis I propose a Bayesian nonparametric estimation method for structural econometric models where the functional parameter of interest describes the economic agent's behavior. The structural parameter is characterized as the solution of a functional equation, or by using more technical words, as the solution of an inverse problem that can be either ill-posed or well-posed. From a Bayesian point of view, the parameter of interest is a random function and the solution to the inference problem is the posterior distribution of this parameter. A regular version of the posterior distribution in functional spaces is characterized. However, the infinite dimension of the considered spaces causes a problem of non continuity of the solution and then a problem of inconsistency, from a frequentist point of view, of the posterior distribution (i.e. problem of ill-posedness). The contribution of this essay is to propose new methods to deal with this problem of ill-posedness. The first one consists in adopting a Tikhonov regularization scheme in the construction of the posterior distribution so that I end up with a new object that I call regularized posterior distribution and that I guess it is solution of the inverse problem. The second approach consists in specifying a prior distribution on the parameter of interest of the g-prior type. Then, I detect a class of models for which the prior distribution is able to correct for the ill-posedness also in infinite dimensional problems. I study asymptotic properties of these proposed solutions and I prove that, under some regularity condition satisfied by the true value of the parameter of interest, they are consistent in a "frequentist" sense. Once I have set the general theory, I apply my bayesian nonparametric methodology to different estimation problems. First, I apply this estimator to deconvolution and to hazard rate, density and regression estimation. Then, I consider the estimation of an Instrumental Regression that is useful in micro-econometrics when we have to deal with problems of endogeneity. Finally, I develop an application in finance: I get the bayesian estimator for the equilibrium asset pricing functional by using the Euler equation defined in the Lucas'(1978) tree-type models.

Efficient certification of feasibility and objective value of linear programs and its applications

The use of linear programming in various areas has increased with the significant improvement of specialized solvers. Linear programs are used as such to model practical problems, or as subroutines in algorithms such as formal proofs or branch-and-cut frameworks. In many situations a certified answer is needed, for example the guarantee that the linear program is feasible or infeasible, or a provably safe bound on its objective value. Most of the available solvers work with floating-point arithmetic and are thus subject to its shortcomings such as rounding errors or underflow, therefore they can deliver incorrect answers. While adequate for some applications, this is unacceptable for critical applications like flight controlling or nuclear plant management due to the potential catastrophic consequences. We propose a method that gives a certified answer whether a linear program is feasible or infeasible, or returns unknown'. The advantage of our method is that it is reasonably fast and rarely answers unknown'. It works by computing a safe solution that is in some way the best possible in the relative interior of the feasible set. To certify the relative interior, we employ exact arithmetic, whose use is nevertheless limited in general to critical places, allowing us to rnremain computationally efficient. Moreover, when certain conditions are fulfilled, our method is able to deliver a provable bound on the objective value of the linear program. We test our algorithm on typical benchmark sets and obtain higher rates of success compared to previous approaches for this problem, while keeping the running times acceptably small. The computed objective value bounds are in most of the cases very close to the known exact objective values. We prove the usability of the method we developed by additionally employing a variant of it in a different scenario, namely to improve the results of a Satisfiability Modulo Theories solver. Our method is used as a black box in the nodes of a branch-and-bound tree to implement conflict learning based on the certificate of infeasibility for linear programs consisting of subsets of linear constraints. The generated conflict clauses are in general small and give good rnprospects for reducing the search space. Compared to other methods we obtain significant improvements in the running time, especially on the large instances.

Approximating method of frames

In this paper, the well-known method of frames approach to the signal decomposition problem is reformulated as a certain bilevel goal-attainment linear least squares problem. As a consequence, a numerically robust variant of the method, named approximating method of frames, is proposed on the basis of a certain minimal Euclidean norm approximating splitting pseudo-iteration-wise method.

Diffusion of linear paraffins in nanoporous silica

The diffusion of hexane, heptane, octane, and decane in nanoporous MCM-41 silica at various temperatures is investigated by the zero-length-column method. The diffusion coefficients are derived by a complete-time-range analysis of desorption curves at different purge flow rates and temperatures. The results show that the calculated low-coverage diffusivity values decrease monotonically, and the derived Henry's law constants increase, as the carbon number of paraffins increases. The study reveals that transport is strongly influenced by intracrystalline diffusion and dominated by the sorbate-sorbent interaction. The diffusion activation energy and adsorption isosteric heat at zero loading increase monotonically with the carbon number of linear paraffins, but their ratio is essentially constant for each adsorbate compound.

Cost-exergy optimisation of linear Fresnel reflectors

This paper presents a new method for the optimisation of the mirror element spacing arrangement and operating temperature of linear Fresnel reflectors (LFR). The specific objective is to maximise available power output (i.e. exergy) and operational hours whilst minimising cost. The method is described in detail and compared to an existing design method prominent in the literature. Results are given in terms of the exergy per total mirror area (W/m2) and cost per exergy (US $/W). The new method is applied principally to the optimisation of an LFR in Gujarat, India, for which cost data have been gathered. It is recommended to use a spacing arrangement such that the onset of shadowing among mirror elements occurs at a transversal angle of 45°. This results in a cost per exergy of 2.3 $/W. Compared to the existing design approach, the exergy averaged over the year is increased by 9% to 50 W/m2 and an additional 122 h of operation per year are predicted. The ideal operating temperature at the surface of the absorber tubes is found to be 300 °C. It is concluded that the new method is an improvement over existing techniques and a significant tool for any future design work on LFR systems