16,281 research outputs found
How export-led growth can lead to take-off
Export-led growth has gained considerable prominence as a model for economic development since its use by East Asian newly industrializing countries. Thus, the question of how it can be used by other countries wishing to industrialize and under what circumstances it can lead to the take-off of an economy is highly relevant for development policy. In light of current macroeconomic imbalances on the global stage, the question of sustainability arises: Is take-off by export-led growth possible without permanent balance-of-trade surpluses? The article gives a brief overview and offers thoughts into various ways in which the impetus of exportled growth for the overall economy might work.development, export-led growth, export base, industrialization, industrial policy, take-off, comparative advantage, new trade theory
An Iterative Model Reduction Scheme for Quadratic-Bilinear Descriptor Systems with an Application to Navier-Stokes Equations
We discuss model reduction for a particular class of quadratic-bilinear (QB)
descriptor systems. The main goal of this article is to extend the recently
studied interpolation-based optimal model reduction framework for QBODEs
[Benner et al. '16] to a class of descriptor systems in an efficient and
reliable way. Recently, it has been shown in the case of linear or bilinear
systems that a direct extension of interpolation-based model reduction
techniques to descriptor systems, without any modifications, may lead to poor
reduced-order systems. Therefore, for the analysis, we aim at transforming the
considered QB descriptor system into an equivalent QBODE system by means of
projectors for which standard model reduction techniques for QBODEs can be
employed, including aforementioned interpolation scheme. Subsequently, we
discuss related computational issues, thus resulting in a modified algorithm
that allows us to construct \emph{near}--optimal reduced-order systems without
explicitly computing the projectors used in the analysis. The efficiency of the
proposed algorithm is illustrated by means of a numerical example, obtained via
semi-discretization of the Navier-Stokes equations
ModHMM: A Modular Supra-Bayesian Genome Segmentation Method
Genome segmentation methods are powerful tools to obtain cell type or tissue-specific genome-wide annotations and are frequently used to discover regulatory elements. However, traditional segmentation methods show low predictive accuracy and their data-driven annotations have some undesirable properties. As an alternative, we developed ModHMM, a highly modular genome segmentation method. Inspired by the supra-Bayesian approach, it incorporates predictions from a set of classifiers. This allows to compute genome segmentations by utilizing state-of-the-art methodology. We demonstrate the method on ENCODE data and show that it outperforms traditional segmentation methods not only in terms of predictive performance, but also in qualitative aspects. Therefore, ModHMM is a valuable alternative to study the epigenetic and regulatory landscape across and within cell types or tissues
On Error Estimation for Reduced-order Modeling of Linear Non-parametric and Parametric Systems
Motivated by a recently proposed error estimator for the transfer function of
the reduced-order model of a given linear dynamical system, we further develop
more theoretical results in this work. Furthermore, we propose several variants
of the error estimator, and compare those variants with the existing ones both
theoretically and numerically. It has been shown that some of the proposed
error estimators perform better than or equally well as the existing ones. All
the error estimators considered can be easily extended to estimate output error
of reduced-order modeling for steady linear parametric systems.Comment: 34 pages, 12 figure
Peer Methods for the Solution of Large-Scale Differential Matrix Equations
We consider the application of implicit and linearly implicit
(Rosenbrock-type) peer methods to matrix-valued ordinary differential
equations. In particular the differential Riccati equation (DRE) is
investigated. For the Rosenbrock-type schemes, a reformulation capable of
avoiding a number of Jacobian applications is developed that, in the autonomous
case, reduces the computational complexity of the algorithms. Dealing with
large-scale problems, an efficient implementation based on low-rank symmetric
indefinite factorizations is presented. The performance of both peer approaches
up to order 4 is compared to existing implicit time integration schemes for
matrix-valued differential equations.Comment: 29 pages, 2 figures (including 6 subfigures each), 3 tables,
Corrected typo
Convergence Analysis of Extended LOBPCG for Computing Extreme Eigenvalues
This paper is concerned with the convergence analysis of an extended
variation of the locally optimal preconditioned conjugate gradient method
(LOBPCG) for the extreme eigenvalue of a Hermitian matrix polynomial which
admits some extended form of Rayleigh quotient. This work is a generalization
of the analysis by Ovtchinnikov (SIAM J. Numer. Anal., 46(5):2567-2592, 2008).
As instances, the algorithms for definite matrix pairs and hyperbolic quadratic
matrix polynomials are shown to be globally convergent and to have an
asymptotically local convergence rate. Also, numerical examples are given to
illustrate the convergence.Comment: 21 pages, 2 figure
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