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Quadrature-based methods for obtaining approximate solutions to nonlinear asset pricing models

by George Tauchen, Robert Hussey - ECONOMETRICA , 1991
"... ..."
Abstract - Cited by 360 (2 self) - Add to MetaCart
Abstract not found

estimates for approximate solutions

by Universität Des Saarlandes, Fachrichtung Mathematik, Michael Bildhauer, Martin Fuchs, Sergey Repin, Michael Bildhauer, Martin Fuchs, Sergey Repin, M. Bildhauer, M. Fuchs, S. Repin
"... The elastic-plastic torsion problem: a posteriori error estimates for approximate solutions ..."
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The elastic-plastic torsion problem: a posteriori error estimates for approximate solutions

The Approximate Solutions of Blasius Equation

by Chun-xuan Jiang
"... We find Blasius function to satisfy the boundary condition f ′ ( ∞) = 1 and obtain the approximate solutions of Blasius equation. ..."
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We find Blasius function to satisfy the boundary condition f ′ ( ∞) = 1 and obtain the approximate solutions of Blasius equation.

Nonlinear Approximation

by Ronald A. DeVore - ACTA NUMERICA , 1998
"... ..."
Abstract - Cited by 970 (40 self) - Add to MetaCart
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Approximate Signal Processing

by S. Hamid Nawab, Alan V. Oppenheim, Anantha P. Chandrakasan, Joseph M. Winograd, Jeffrey T. Ludwig , 1997
"... It is increasingly important to structure signal processing algorithms and systems to allow for trading off between the accuracy of results and the utilization of resources in their implementation. In any particular context, there are typically a variety of heuristic approaches to managing these tra ..."
Abstract - Cited by 516 (2 self) - Add to MetaCart
these tradeoffs. One of the objectives of this paper is to suggest that there is the potential for developing a more formal approach, including utilizing current research in Computer Science on Approximate Processing and one of its central concepts, Incremental Refinement. Toward this end, we first summarize a

Finite state Markov-chain approximations to univariate and vector autoregressions

by George Tauchen - Economics Letters , 1986
"... The paper develops a procedure for finding a discrete-valued Markov chain whose sample paths approximate well those of a vector autoregression. The procedure has applications in those areas of economics, finance, and econometrics where approximate solutions to integral equations are required. 1. ..."
Abstract - Cited by 472 (0 self) - Add to MetaCart
The paper develops a procedure for finding a discrete-valued Markov chain whose sample paths approximate well those of a vector autoregression. The procedure has applications in those areas of economics, finance, and econometrics where approximate solutions to integral equations are required. 1.

On approximative solutions of multistopping problems

by Andreas Faller, Ludger Rüschendorf
"... We consider multistopping problems for discrete time sequences as well as for continuous time Poisson processes which serve as limiting models for the discrete time problem. The choice of m-stopping times is allowed and the aim is to maximize the expected value of the best of the m stops. The optima ..."
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. The optimal m-stopping curves of the Poisson process are determined by differential equations of first order and allow the construction of approximative solutions of the discrete time m-stopping problem.

Approximate Solution of the Representability Problem

by A. I. Panin , 1999
"... ABSTRACT: Approximate solution of the ensemble representability problem for density operators of arbitrary order is obtained. This solution is closely related to the “Q condition ” of A. J. Coleman. The representability conditions are formulated in orbital representation and are easy for computer im ..."
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ABSTRACT: Approximate solution of the ensemble representability problem for density operators of arbitrary order is obtained. This solution is closely related to the “Q condition ” of A. J. Coleman. The representability conditions are formulated in orbital representation and are easy for computer

Approximate Solutions to Markov Decision Processes

by Geoffrey J. Gordon , 1999
"... One of the basic problems of machine learning is deciding how to act in an uncertain world. For example, if I want my robot to bring me a cup of coffee, it must be able to compute the correct sequence of electrical impulses to send to its motors to navigate from the coffee pot to my office. In fact, ..."
Abstract - Cited by 82 (10 self) - Add to MetaCart
like the above one quickly and reliably. Unfortunately, the world is often so complicated that it is difficult or impossible to find the optimal sequence of actions to achieve a given goal. So, in order to scale our learners up to real-world problems, we usually must settle for approximate solutions

Approximate Riemann Solvers, Parameter Vectors, and Difference Schemes

by P. L. Roe - J. COMP. PHYS , 1981
"... Several numerical schemes for the solution of hyperbolic conservation laws are based on exploiting the information obtained by considering a sequence of Riemann problems. It is argued that in existing schemes much of this information is degraded, and that only certain features of the exact solution ..."
Abstract - Cited by 959 (2 self) - Add to MetaCart
Several numerical schemes for the solution of hyperbolic conservation laws are based on exploiting the information obtained by considering a sequence of Riemann problems. It is argued that in existing schemes much of this information is degraded, and that only certain features of the exact solution
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