A least-square infinite series approximation (L-SISA) technique is proposed for modeling amplitude modulated (AM) sinusoidal components of naturally occurring signals, such as those produced by traditional musical instruments. Each AM sinusoid is iteratively extracted using an analysis-by-synthesis technique and the problem of parameter estimation is linearised for least-square approximation th...

In the paper, a technique of the numerical inversion of multidimensional Laplace transforms (nD NILT), based on a complex Fourier series approximation is elaborated in light of a possible ralative error achievable. The detailed error analysis shows a relationship between the numerical integration of a multifold Bromwich integral and a complex Fourier series approximation, and leads to a novel f...

We study in this paper the existence and approximation of solutions of variational inequalities involving generalized pseudo-contractive mappings in Banach spaces. The convergence analysis of a proposed hybrid iterative method for approximating common zeros or fixed points of a possibly infinitely countable or uncountable family of such operators will be conducted within the conceptual framewor...

The efficiency of hierarchical matrices is based on the approximate evaluation of usual matrix operations. The introduced approximation error may, however, lead to a loss of important matrix properties. In this article we present a technique which preserves the positive definitness of a matrix independently of the approximation quality. The importance of this technique is illustrated by an elli...

We develop a discrete-time approximation technique dealing with the time-cost trade-off problem in PERT networks. It is assumed that the activity durations are independent random variables with generalized Erlang distributions, in which the mean duration of each activity is a non-increasing function of the amount of resource allocated to it. It is also assumed that the amount of resource alloca...

We extend the “policy rollout” sampling technique for Markov decision processes to Markov games, and provide an approximation result guaranteeing that the resulting sampling-based policy is closer to the Nash equilibrium than the underlying base policy. This improvement is achieved with an amount of sampling that is independent of the state-space size. We base our approximation result on a more...

Theoretical models of single-file transport in a homogeneous channel are considered. Three levels of channel populations were specified for which different approximations could be used. The results of these approximations are in good agreement with the results of a computer experiment (Aityan and Portnov 1986). At low populations, the pair correlation functions were negligibly small and allowed...

We present a new Lagrangian-based iterative technique for rate{distortion optimization under multiple rate constraints. We show how for sets of \lin-ear" constraints this technique can be proven to be optimal up to a convex hull approximation. As an application we consider the problem of optimal buuer-constrained bit allocation. Our technique can be used to nd an excellent approximation to the ...

In the previous few lectures we have seen examples of LP-rounding, a method for obtaining approximation algorithms that involves solving a linear programming relaxation of the problem at hand and rounding the solution. In the last lecture we also discussed the basic theory of LP-duality. Today we will apply this theory to obtain a second LP-based technique for obtaining approximation algorithms...

In this paper, we propose a new model-order reduction technique for linear dynamic systems. The idea behind this technique is to transform the dynamic system function from the s-domain into the z-domain via the bilinear transformation, then use Prony’s [1, 2] or Shank’s [3] least-squares approximation methods instead of the commonly employed Padé approximation method, and finally transform the ...