984 resultados para Global convergence


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The paper deals with the basic problem of adjusting a matrix gain in a discrete-time linear multivariable system. The object is to obtain a global convergence criterion, i.e. conditions under which a specified error signal asymptotically approaches zero and other signals in the system remain bounded for arbitrary initial conditions and for any bounded input to the system. It is shown that for a class of up-dating algorithms for the adjustable gain matrix, global convergence is crucially dependent on a transfer matrix G(z) which has a simple block diagram interpretation. When w(z)G(z) is strictly discrete positive real for a scalar w(z) such that w-1(z) is strictly proper with poles and zeros within the unit circle, an augmented error scheme is suggested and is proved to result in global convergence. The solution avoids feeding back a quadratic term as recommended in other schemes for single-input single-output systems.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Despite striking differences in climate, soils, and evolutionary history among diverse biomes ranging from tropical and temperate forests to alpine tundra and desert, we found similar interspecific relationships among leaf structure and function and plant growth in all biomes. Our results thus demonstrate convergent evolution and global generality in plant functioning, despite the enormous diversity of plant species and biomes. For 280 plant species from two global data sets, we found that potential carbon gain (photosynthesis) and carbon loss (respiration) increase in similar proportion with decreasing leaf life-span, increasing leaf nitrogen concentration, and increasing leaf surface area-to-mass ratio. Productivity of individual plants and of leaves in vegetation canopies also changes in constant proportion to leaf life-span and surface area-to-mass ratio. These global plant functional relationships have significant implications for global scale modeling of vegetation–atmosphere CO2 exchange.

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In this work we give su±cient conditions for k-th approximations of the polynomial roots of f(x) when the Maehly{Aberth{Ehrlich, Werner-Borsch-Supan, Tanabe, Improved Borsch-Supan iteration methods fail on the next step. For these methods all non-attractive sets are found. This is a subsequent improvement of previously developed techniques and known facts. The users of these methods can use the results presented here for software implementation in Distributed Applications and Simulation Environ- ments. Numerical examples with graphics are shown.

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The debate associated with the qualifications of business school faculty has raged since the 1959 release of the Gordon–Howell and Pierson reports, which encouraged business schools in the USA to enhance their legitimacy by increasing their faculties’ doctoral qualifications and scholarly rigor. Today, the legitimacy of specific faculty qualifications remains one of the most discussed topics in management education, attracting the interest of administrators, faculty, and accreditation agencies. Based on new institutional theory and the institutional logics perspective, this paper examines convergence and innovation in business schools through an analysis of faculty hiring criteria. The qualifications examined are academic degree, scholarly publications, teaching experience, and professional experience. Three groups of schools are examined based on type of university, position within a media ranking system, and accreditation by the Association to Advance Collegiate Schools of Business. Data are gathered using a content analysis of 441 faculty postings from business schools based in the USA over two time periods. Contrary to claims of global convergence, we find most qualifications still vary by group, even in the mature US market. Moreover, innovative hiring is more likely to be found in non-elite schools.

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A novel global optimization method based on an Augmented Lagrangian framework is introduced for continuous constrained nonlinear optimization problems. At each outer iteration k the method requires the epsilon(k)-global minimization of the Augmented Lagrangian with simple constraints, where epsilon(k) -> epsilon. Global convergence to an epsilon-global minimizer of the original problem is proved. The subproblems are solved using the alpha BB method. Numerical experiments are presented.

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Purpose - The purpose of this paper is to examine the accounting education systems in three countries - Australia, Japan and Sri Lanka - to inform the development and testing (by application) of a Global Model of Accounting Education.

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In recent times the Douglas–Rachford algorithm has been observed empirically to solve a variety of nonconvex feasibility problems including those of a combinatorial nature. For many of these problems current theory is not sufficient to explain this observed success and is mainly concerned with questions of local convergence. In this paper we analyze global behavior of the method for finding a point in the intersection of a half-space and a potentially non-convex set which is assumed to satisfy a well-quasi-ordering property or a property weaker than compactness. In particular, the special case in which the second set is finite is covered by our framework and provides a prototypical setting for combinatorial optimization problems.

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Image-based visual servo (IBVS) is a simple, efficient and robust technique for vision-based control. Although technically a local method in practice it demonstrates almost global convergence. However IBVS performs very poorly for cases that involve large rotations about the optical axis. It is well known that re-parameterizing the problem by using polar, instead of Cartesian coordinates, of feature points overcomes this limitation. First, simulation and experimental results are presented to show the complementarity of these two parameter-izations. We then describe a new hybrid visual servo strategy based on combining polar and Cartesian image Jacobians. © 2009 IEEE.

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In this paper, general order conditions and a global convergence proof are given for stochastic Runge Kutta methods applied to stochastic ordinary differential equations ( SODEs) of Stratonovich type. This work generalizes the ideas of B-series as applied to deterministic ordinary differential equations (ODEs) to the stochastic case and allows a completely general formalism for constructing high order stochastic methods, either explicit or implicit. Some numerical results will be given to illustrate this theory.