The purpose of this study is to present an approximate numerical method for solving high order linear Fredholm-Volterra integro-differential equations in terms of rational Chebyshev functions under the mixed conditions. The method is based on the approximation by the truncated rational Chebyshev series. Finally, the effectiveness of the method is illustrated in several numerical examples. The p...

In this paper, the numerical technique based on hybrid Bernoulli and Block-Pulse functions has been developed to approximate the solution of system of linear Volterra integral equations. System of Volterra integral equations arose in many physical problems such as elastodynamic, quasi-static visco-elasticity and magneto-electro-elastic dynamic problems. These functions are formed by the hybridi...

Causality requires that the ~anti!commutator of two interacting field operators vanishes for spacelike coordinate differences. This implies that the Fourier transform of the spectral function of this quantum field should vanish in the spacelike domain. We find that this requirement imposes some constraints on the use of resummed propagators in high temperature gauge theory. @S0556-2821~96!02418-6#

Let A 1 , A 2 ,. .. , A n be events in some probability space. The approximate inclusion-exclusion problem, due to Linial and Nisan (1990), is to estimate Pr[A 1 ∪· · ·∪A n ] given Pr[ i∈S A i ] for all |S | k. Kahn et al. (1996) solve this problem optimally for each k. We study the following more general question: given Pr[ i∈S A i ] for all |S | k, estimate Pr the number of events among A 1 ,...

Approximations are commonly employed to find approximate solutions to the Einstein equations. These solutions, however, are usually only valid in some specific spacetime region. A global solution can be constructed by gluing approximate solutions together, but this procedure is difficult because discontinuities can arise, leading to large violations of the Einstein equations. In this paper, we ...

The rule of an approximate identity is as follows: A function f which has to be approximated is convolved with a kernel Kδ for some δ. If the kernel satisfies certain conditions then the convolutions converge in a certain limit such as δ → 0+ to f . Note that approximate identities for scalar function on balls in R are studied e.g. in [14]. Further works on localizing kernels, like scaling func...

Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuristic is not always available. We propose a new approach to learning heuristic functions from previously solved problem instances in a given domain. Our approach is based on approximate linear programming, commonly used ...

The evaluation of the quality of solutions is usually very time-consuming in design optimization. Therefore, time-efficient approximate models can be particularly beneficial for the evaluation when evolutionary algorithms are applied. In this paper, the convergence property of an evolution strategy (ES) with neural network based fitness evaluations is investigated. It is found that the evolutio...