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In this paper, a symbolic dynamical model of the average queue size of the random early detection (RED) algorithm is proposed. The conditions for both the system parameters and the initial conditions that the average queue size of the RED algorithm would converge to a fixed point are derived. These results are useful for network engineers to design both the system parameters and the initial conditions so that internet networks can achieve a good performance. [ABSTRACT FROM AUTHOR]

In this paper, a new frame rate up-conversion (FRC) using Backward Multiple Reference Frame Motion (BMRF) compensated interpolation (MCI) algorithm is proposed. The BMRF algorithm has been compared with two most common MCI methods, Temporal Linear (TLIN) and Bidirectional MCI (BID) used in FRC, in the aspect of PSNR, perceptual quality, and computational complexity. The simulation results clearly showed that BMRF presented a trade-off solution between computation and interpolation quality. By using simple weighted frame interpolation between multiple frames, it reduced computation rapidly while keeping similar interpolation quality when compared to the BID method. The simplicity of the BMRF algorithm made it suitable for either software or hardware implementation essential for real-time FRC applications. [ABSTRACT FROM AUTHOR]

In this paper, a lattice ℓ-step ahead output uncertainty prediction algorithm is presented. The proposed prediction scheme is applicable to linear, stable, auto-regressive (AR) systems. The uncertainty predictors utilize the structure of the lattice filters. Subject to the saturation limits of the excitation signal, the measurement of the system output, and the a priori bounds of the reflection coefficients, the set of the feasible predicted output variables is computed. The suggested scheme is recursively computed over an ℓ-step ahead future time window, while the prediction uncertainty intervals are similarly computed over the lattice stages, regarding the forward and the backward prediction errors. Simulation results are presented that prove the efficacy of the employed lattice uncertainty predictors. [ABSTRACT FROM AUTHOR]

By analyzing the dynamic behaviors of the transiently chaotic neural network and greedy heuristic for the maximum independent set (MIS) problem, we present an improved transiently chaotic neural network for the MIS problem in this paper. Extensive simulations are performed and the results show that this proposed transiently chaotic neural network can yield better solutions to p-random graphs than other existing algorithms. The efficiency of the new model is also confirmed by the results on the complement graphs of some DIMACS clique instances in the second DIMACS challenge. Moreover, the improved model uses fewer steps to converge to stable state in comparison with the original transiently chaotic neural network. [ABSTRACT FROM AUTHOR]

There is an important interest in compensating thermally induced errors of modular tool systems to improve the manufacturing accuracy. In this paper, we test the hypothesis whether we can predict such thermal displacements by using a nonlinear regression analysis, namely the alternating conditional expectation algorithm (ACE [Breiman & Friedman, 1985]), reliably. The data analyzed were generated by two different finite element spindle models of modular tool systems. As the main result, we find that the ACE-algorithm is a powerful tool to model the relation between temperatures and displacements. The maximal correlation is larger than 0.999 in both cases, which demonstrates the suitability of the ACE algorithm. Furthermore, preconditions for the applicability of this approach, such as the length and the support of measured data sets, are studied. Hence, this approach seems to be promising for the application to real modular tool systems. [ABSTRACT FROM AUTHOR]

In this paper, we present a new approach to geometrical modeling which allows the user to easily characterize and control the shape defined to a closed surface. We will focus on dealing with the shape's topological, morphological and geometrical properties separately. To do this, we have based our work on the following observations concerning surfaces defined by control-points, and implicit surfaces with skeleton. They both provide complementary approaches to the surface's deformation, and both have specific advantages and limits. We thus attempted to conceive a model which integrates the local and geometrical characterization induced by the control points, as well as the representation of the morphology given by the skeleton. Knowing that the lattice of control points is close to the surface and that the skeleton is centered in the related shape, we thought of a 3-layer model. The transition layer separates the local geometrical considerations from those linked to the global morphology. We apply our model to shape design in order to modify an object in an interactive and ergonomic way, as well as to reconstruction which allows better shape understanding. To do so, we present the algorithms related to these processes. [ABSTRACT FROM AUTHOR]

A polygonal approximation captures the essential features of a digital planar curve and yields a compact representation. Those points of the digital curve that carry vital information about the shape of the curve form the vertices of the approximating polygon and are called significant vertices. In this paper, we present a genetic algorithm-based approach to locate a specified number of significant points, such that the approximation error between the original curve and its polygonal version obtained by joining the adjacent significant points is minimized. By using a priori knowledge about the shape of the curve we confine our search to only those points of the curve that have the potential of qualifying as significant points. We also incorporate chromosome differentiation to improve upon the effectiveness of the search in arriving at a near-optimal polygonal approximation. Finally, we show that the proposed method performs remarkably well when evaluated in terms of the metrics available for assessing the goodness of a polygonal approximation algorithm. [ABSTRACT FROM AUTHOR]