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An algorithm that is capable not only of tracking multiple targets but also of "track management"-meaning that it does not need to know the number of targets as a user input-is of considerable interest. In this paper we devise a recursive track-managed filter via a quantized state-space ("bin") model. In the limit, as the discretization implied by the bins becomes as refined as possible (infinitesimal bins) we find that the filter equations are identical to Mahier's probability hypothesis density (PHD) filter, a novel trackmanaged filtering scheme that is attracting increasing attention. Thus, one contribution of this paper is an interpretation of, if not the PHD itself, at least what the PHD is doing. This does offer some intuitive appeal, but has some practical use as well: with this model it is possible to identify the PHD's "target-death" problem, and also the statistical inference structures of the PHD filters. To obviate the target death problem, PHD originator Mahler developed a new "cardinalized" version of PHD (CPHD). The second contribution of this paper is to extend the "bin-occupancy" model such that the resulting recursive filter is identical to the cardinalized PHD filter. [ABSTRACT FROM AUTHOR]

The goal of this paper is to solve mathematical model equations on solid tumour growth and compute their parameter values by applying growth rates of prostate cancer cell lines in vivo. For these computations, we investigate previously developed C3(1)/Tag transgenic models of prostate cancer. To make the computations fast, we have constructed an algorithm, which is based on small amounts of spatial grid-points and obtained a correspondence between the in vivo growth of tumours and the solutions of the model equations. [ABSTRACT FROM AUTHOR]

Approximations of a concept in rough set theory induce rules and need to update for dynamic data mining and related tasks. Most existing incremental methods based on the classical rough set model can only be used to deal with the categorical data. This paper presents a new dynamic method for incrementally updating approximations of a concept under neighborhood rough sets to deal with numerical data. A comparison of the proposed incremental method with a nonincremental method of dynamic maintenance of rough set approximations is conducted by an extensive experimental evaluation on different data sets from UCI. Experimental results show that the proposed method effectively updates approximations of a concept in practice. © 2012 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

This paper investigates backscatter data for the inverse obstacle problem in impedance tomography, when the obstacles are small. It is shown that under this circumstance the backscatter data are close approximations of a rational function that has second or fourth order poles at the locations of the obstacles. Furthermore, a numerical method is presented to locate the obstacles via the poles of certain Laurent-Padé approximations. Numerical experiments explore the potential of this algorithm also for extended obstacles, taking into consideration that the problem is severely ill-posed. [ABSTRACT FROM AUTHOR]

Further progress in pair-density functional theory (sometimes called 2-DFT) hinges on the development of computationally facile and quantitatively accurate models for the kinetic energy functional. In this paper we perform computational tests for two of the simplest models, the generalized Weizsäcker kinetic energy functional and its spin-resolved extension. Both of these models perform very poorly for atoms. The higher-order Weizsäcker functionals (based on the three-electron distribution function) perform better, but are still not successful. This suggests that an alternative approach for designing kinetic energy functionals of the pair density is needed. [ABSTRACT FROM AUTHOR]

In this paper, we study the quadratic model updating problems by using symmetric low-rank correcting, which incorporates the measured model data into the analytical quadratic model to produce an adjusted model that matches the experimental model data, and minimizes the distance between the analytical and updated models. We give a necessary and sufficient condition on the existence of solutions to the symmetric low-rank correcting problems under some mild conditions, and propose two algorithms for finding approximate solutions to the corresponding optimization problems. The good performance of the two algorithms is illustrated by numerical examples. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, we prove the following two results that expose some combinatorial limitations to list decoding Given n distinct elements α1,…,αn, from a field F, and n subsets S1,…Sn of F each of size at most l, the list decoding algorithm of Guruswami and Sudan can in polynomial time output all polynomials p of degree at most k that satisfy p(αi] ϵ Si for every i, as long as l ≤ [n⁄k]. We show that the performance of this algorithm is the best possible in a strong sense; specifically, when l = [n⁄k], the list of output polynomials can be superpolynomially large in n. For Reed-Solomon codes of block length n and dimension k + 1 where k = nδ for small enough δ, we exhibit an explicit received word with a superpolynomial number of Reed-Solomon codewords that agree with it on (2 - ϵ)k locations, for any desired ϵ ≥ 0 (agreement of k is trivial to achieve). Such a bound was known earlier only for a nonexplicit center. Finding explicit bad list decoding configurations is of significant interest—for example, the best known rate versus distance tradeoff, due to Xing, is based on a bad list decoding configuration for algebraic-geometric codes, which is unfortunately not explicitly known. [ABSTRACT FROM AUTHOR]

Abstract: Fractional order PI and PID controllers are the most common fractional order controllers used in practice. In this paper, a simple analytical method is proposed for tuning the parameters of these controllers. The proposed method is useful in designing fractional order PI and PID controllers for control of complicated fractional order systems. To achieve the goal, at first a reduction technique is presented for approximating complicated fractional order models. Then, based on the obtained reduced models some analytical rules are suggested to determine the parameters of fractional order PI and PID controllers. Finally, numerical results are given to show the efficiency of the proposed tuning algorithm. [Copyright &y& Elsevier]

We show that Tsirelson's problem concerning the set of quantum correlations and Connes' embedding problem on finite approximations in von Neumann algebras (known to be equivalent to Kirchberg's QWEP conjecture) are essentially equivalent. Specifically, Tsirelson's problem asks whether the set of bipartite quantum correlations generated between tensor product separated systems is the same as the set of correlations between commuting C*-algebras. Connes' embedding problem asks whether any separable II1 factor is a subfactor of the ultrapower of the hyperfinite II1 factor. We show that an affirmative answer to Connes' question implies a positive answer to Tsirelson's. Conversely, a positive answer to a matrix valued version of Tsirelson's problem implies a positive one to Connes' problem. [ABSTRACT FROM AUTHOR]

Two modified blind equalization algorithms are analyzed for performance. These algorithms add a constellation-matched error term to the cost functions of the generalized Sato and multimodulus algorithms. The dynamic convergence behavior and steady-state performance of these algorithms, and of a related version of the constant modulus algorithm, are characterized; The analysis establishes the improved performance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

We propose a robust interpolation algorithm for model-based spectral analysis. Instead of estimating the spectral model directly, the so-called ha If spectrum, which has a one-to-one relationship with the spectrum through standard spectral decomposition, is estimated using an interpolation approach. The interpolation data consists of the values and the derivatives of the half spectrum function at a set of user-specified points, and can be easily estimated using an input-to-state filter. Our algorithm allows a large number of noisy interpolation data to be used to optimally fit a half spectrum function of a fixed order. The capability of handling large number of interpolation data makes our algorithm robust to the inherent finite sample noise in the interpolation data. The algorithm involves solving some least-squares problems and semidefinite programming problems, and is thus numerically efficient. Numerical tests show that our algorithm gives very reliable spectral estimates. [ABSTRACT FROM AUTHOR]

A new identification algorithm is introduced for the Hammerstein model consisting of a nonlinear static function followed by a linear dynamical model. The nonlinear static function is characterised by using the Bezier–Bernstein approximation. The identification method is based on a hybrid scheme including the applications of the inverse of de Casteljau's algorithm, the least squares algorithm and the Gauss–Newton algorithm subject to constraints. The related work and the extension of the proposed algorithm to multi-input multi-output systems are discussed. Numerical examples including systems with some hard nonlinearities are used to illustrate the efficacy of the proposed approach through comparisons with other approaches. [ABSTRACT FROM AUTHOR]

Understanding the behavior of an idle time of a limited resource is the key to increase productivity in service operations. When the system consists of nonexponential properties of time distributions it becomes difficult to provide results for the general case. We derive the MacLaurin series for the moments of the idle time with respect to the parameters in the service time and interarrival time distributions for aGI/G/1 queue. The light traffic derivatives are obtained to investigate the quality of a well-known MacLaurin series. The expected error bound under this approach is identified. The coefficients in these series are expressed in terms of the derivatives of the interarrival time density function evaluated at zero and the moments of the service time distribution, which can be easily calculated through a simple recursive procedure. The result for the idle period is easily taken as input to the calculation of other performance measures of the system, e.g., cycle time or interdeparture time distributions. Numerical examples are given to illustrate these results. [ABSTRACT FROM AUTHOR]

We are concerned with the main multiserver retrial queue of M/M/c type with exponential repeated attempts. It is known that an analytical solution of this queueing model is difficult and does not lead to numerical implementation. Based on appropriate understanding of the physical behavior, an efficient and numerically stable algorithm for computing the stationary distribution of the system state is developed. Numerical calculations are done to compare our approach with the existing approximations. [ABSTRACT FROM AUTHOR]

Reliability studies give rise to families of distribution functions F[sup (n)] defined recursively by the repeated convolution of a distribution function F with itself according to the scheme F[sup (1)](t) = F(t), F[sup (n+1)](t) = ∫[sup t, sub 0]F[sup (n)](1-x)F'(x)dx, n>1, where F' is the derivative of F, and is usually given by a p.d,f, ∫. In particular, many systems characteristics are defined in terms of integrals of the form ∫[sup 1, sub 0]P[sup (s)](t- x)Q[sup (r)]'(x)dx where P[sup (s)] and Q[sup (r)] are the sth and rth members of families generated from distribution functions P and Q, not necessarily distinct. It is seldom possible or convenient to express the F[sup (n)] in analytical form. An algorithm based on cubic spline interpolation is given here for recursively generating continuous numerical approximations to the F[sup (n)] in a form which allows them to be convoluted together to provide useful approximation to the second of the above integrals. [ABSTRACT FROM AUTHOR]

Numerical models of holograms are available but their evaluation is a very computationally intensive task. We present an acceleration algorithm for optical field synthesis suitable for the reduced occlusion method of hologram synthesis. The acceleration uses an approximation that is designed for a field programmable gate array (FPGA) and therefore it mostly uses fixed point numbers. The work describes the approximation, its fixed-point modification, and the resulting FPGA structure. The results presented show that the solution produces high-quality holograms in a significantly reduced time due to efficient FPGA implementation. [ABSTRACT FROM AUTHOR]