Analytic and computational analysis of the discrete-time GI/D-MSP/1 queue using roots

This paper presents a simple closed-form analysis for evaluating system-length distributions at various epochs of the discrete-time GI/D-MSP/1 queue. The proposed analysis is based on roots of the associated characteristic equation of the vector-generating function of system-length distribution at prearrival epochs. We provide the steady-state system-length distribution at random epoch by using the classical argument based on Markov renewal theory. The queueing-time distribution has also been investigated. Numerical aspects have been tested for a variety of interarrival- and service-time distributions and a sample of numerical outputs is presented.     

On continued fraction expansion of real roots of polynomial systems, complexity and condition numbers

We elaborate on a correspondence between the coefficients of a multivariate polynomial represented in the Bernstein basis and in a tensor-monomial basis, which leads to homography representations of polynomial functions that use only integer arithmetic (in contrast to the Bernstein basis) and are feasible over unbounded regions. Then, we study an algorithm to split this representation and obtain a subdivision scheme for the domain of multivariate polynomial functions. This implies a new algorithm for real root isolation, MCF, that generalizes the Continued Fraction (CF) algorithm of univariate polynomials.A partial extension of Vincent’s Theorem for multivariate polynomials is presented, which allows us to prove the termination of the algorithm. Bounding functions, projection and preconditioning are employed to speed up the scheme. The resulting isolation boxes have optimized rational coordinates, corresponding to the first terms of the continued fraction expansion of the real roots. Finally, we present new complexity bounds for a simplified version of the algorithm in the bit complexity model, and also bounds in the real RAM model for a family of subdivision algorithms in terms of the real condition number of the system. Examples computed with our C++ implementation illustrate the practical aspects of our method.     

On computational issues for stability analysis of LPV systems using parameter‐dependent Lyapunov functions and LMIs

Robust stability analysis of linear systems subject to time‐varying parameters is investigated. The objective is to discuss some computational issues associated with solving stability conditions based on parameter‐dependent Lyapunov functions by means of linear matrix inequalities (LMIs), which are exacerbated as the quantity of time‐varying parameters increases. A new solution related to the inclusion of the time derivatives of the parameters is proposed, improving the computational cost without resulting in much conservatism. The time complexity to solve the LMIs reduces from factorial to linear. Numerical examples are provide to illustrate the advantages of the proposed methodology.     

On the exact asymptotics for the stationary sojourn time distribution in a tandem of queues with light-tailed service times

We study the asymptotics of the stationary sojourn time Z of a “typical customer” in a tandem of single-server queues. It is shown that in a certain “intermediate” region of light-tailed service time distributions, Z may take a large value mostly due to a large value of a single service time of one of the customers. Arguments used in the paper also allow us to obtain an elementary proof of the logarithmic asymptotics for the tail distribution of the stationary sojourn time in the whole class of light-tailed distributions.     

TARGET expert systems for analysis and trouble resolution of remote telecommunications equipment

Current trends in technology and operational procedures related to telecommunications equipment present opportunities in which expert systems can play an important role in meeting the needs and objectives of telephone operating companies. The TARGET (Truoble Analysis and Resolution Guided by Expert Techniques) Expert Systems are a set of expert systems that extend the span of knowledge of telephone company personnel in the areas of telecommunication equipment troubleshooting and maintenance. The expert systems upgrade troubleshooting and maintenance performance and allow personnel to perform troubleshooting and maintenance tasks that they otherwise would not have the expertise to perform or to perform well. The initial systems will provide expert knowledfe for troubleshooting remotely sited equipment.     

高效缩1码模2n+1加法器设计与优化

针对目前存在的缩1码模2~n+1加法器的优缺点,设计出一个有效的基于进位选择的缩1码模2~n+1加法器。在模加法器的进位计算中,采用进位选择计算代替传统的进位计算,进位计算前缀运算量明显减少。分析和实验结果表明,对于比较大的n值,进位选择缩1码模2~n+1加法器在保持较高运算速度的前提下,有效地提高了集成度。     

MAX(1)和MARG(1)中公式改名的复杂性

改名是一个将变元映射到变元本身或它的补的函数,变元改名是公式变元集合上的一个置换,文字改名是一个改名和一个变元改名的组合.研究CNF公式的改名有助于改进DPLL算法.考虑判定问题"对于给定的CNF公式H和F是否存在一个变元(或文字)改名ψ使得ψ(H)=F?"的计算复杂性.MAX(1)和MARG(1)是极小不可满足公式的两个子类,这两个子类中的公式可以用树表示.树同构的判定问题在线性时间内是可解的.证明了对于MAX(1)和MARG(1)中的公式,文字改名问题在线性时间内可解,变元改名问题在平方次时间内可解.     

A computational method for solving optimal control and parameter estimation of linear systems using Haar wavelets

In this article, a computational method based on Haar wavelet in time-domain for solving the problem of optimal control of the linear time invariant systems for any finite time interval is proposed. Haar wavelet integral operational matrix and the properties of Kronecker product are utilized to find the approximated optimal trajectory and optimal control law of the linear systems with respect to a quadratic cost function by solving only the linear algebraic equations. It is shown that parameter estimation of linear system can be done easily using the idea proposed. On the basis of Haar function properties, the results of the article, which include the time information, are illustrated in two examples.     

On busy period and sojourn time distributions in the M/G/1-EPS queue with catastrophes

We derive the Laplace-Stiltjes transforms of busy period and sojourn time distributions in the M/G/1 queue with egalitarian processor sharing (EPS) and the possibility of (external) catastrophes. Each arrival of the catastrophes immediately removes all the positive jobs (and hence unfinished work) in this non work-conserving queueing system. One of the main results is obtained by means of the so-called method of decomposition into delay elements introduced by the first author.     

L1 analysis and design of sampled-data systems

The focus of this work is L₁-optimal control of sampled-data systems. A converging approximation procedure is derived to compute the L_∞-induced norm of closed-loop finite-dimensional linear time-invariant (LTI) sampled-data systems. An approximation method is developed to synthesize L₁-optimal sampled-data regulators. Finally, an example is provided that illustrates the L₁ analysis and design techniques presented     

Steady state analysis and computation of the GI/M/1/L queue with multiple working vacations and partial batch rejection

This paper analyzes a finite-buffer bulk-arrival bulk-service queueing system with multiple working vacations and partial batch rejection in which the inter-arrival and service times are, respectively, arbitrarily and exponentially distributed. Using the supplementary variable and the embedded Markov chain techniques, we obtain the waiting queue-length distributions at pre-arrival and arbitrary epochs. We also present Laplace–Stiltjes transform of the actual waiting-time distribution in the queue. Finally, several performance measures and a variety of numerical results in the form of tables and graphs are discussed.     

Necessary and sufficient conditions on Q ( = C( I + PC)) for stabilization of the linear feedback system S(P, C)

We find the following necessary and sufficient conditions for Q (:=C(I+PC)⁻¹) to -stabilize the standard linear time-invariant unity feedback system S(P, C) where P has the l.c.f. (D_pl, N_pl) and the r.c.f. (N_pr, D_pr); and is a principal ideal domain. (i) Q must have elements in (ii) (resp. (iii)) Q must factorize in with D_pr, (resp. D_pl) as a left (resp. right) factor and (iv) (I – QP) must factor in with D_pr, as a left factor.     

Problem solution sustenance in XCS: Markov chain analysis of niche support distributions and the impact on computational complexity

Michigan-style learning classifier systems iteratively evolve a distributed solution to a problem in the form of potentially overlapping subsolutions. Each problem niche is covered by subsolutions that are represented by a set of predictive rules, termed classifiers. The genetic algorithm is designed to evolve classifier structures that together cover the whole problem space and represent a complete problem solution. An obvious challenge for such an online evolving, distributed knowledge representation is to continuously sustain all problem subsolutions covering all problem niches, that is, to ensure niche support. Effective niche support depends both on the probability of reproduction and on the probability of deletion of classifiers in a niche. In XCS, reproduction is occurrence-based whereas deletion is support-based. In combination, niche support is assured effectively. In this paper we present a Markov chain analysis of the niche support in XCS, which we validate experimentally. Evaluations in diverse Boolean function settings, which require non-overlapping and overlapping solution structures, support the theoretical derivations. We also consider the effects of mutation and crossover on niche support. With respect to computational complexity, the paper shows that XCS is able to maintain (partially overlapping) niches with a computational effort that is linear in the inverse of the niche occurrence frequency.

On the choice of importance distributions for unconstrained and constrained state estimation using particle filter

Recursive state estimation of constrained nonlinear dynamical system has attracted the attention of many researchers in recent years. For nonlinear/non-Gaussian state estimation problems, particle filters have been widely used (Arulampalam et al. [1]). As pointed out by Daum [2], particle filters require a proposal distribution and the choice of proposal distribution is the key design issue. In this paper, a novel approach for generating the proposal distribution based on a constrained Extended Kalman filter (C-EKF), Constrained Unscented Kalman filter (C-UKF) and constrained Ensemble Kalman filter (C-EnkF) has been proposed. The efficacy of the proposed state estimation algorithms using a particle filter is illustrated via a successful implementation on a simulated gas-phase reactor, involving constraints on estimated state variables and another example problem, which involves constraints on the process noise (Rao et al. [10]). We also propose a state estimation scheme for estimating state variables in an autonomous hybrid system using particle filter with Unscented Kalman filter as a proposal and unconstrained Ensemble Kalman filter (EnKF) as a proposal. The efficacy of the proposed state estimation scheme for an autonomous hybrid system is demonstrated by conducting simulation studies on a three-tank hybrid system. The simulation studies underline the crucial role played by the choice of proposal distribution in formulation of particle filters.     

Generalization of rectangular element stiffness matrix and thermal load vector associated with a0 + a1x + a2y + a3xy type interpolation rule

Explicit expressions for the element stiffness matrix K and element load vector p for the rectangular plane-stress and plane-strain finite elements associated with Ψ(x, y) = a₀ + a₁x + a₂y + a₃xy type interpolation rule are given for the general anisotropic material in xy-planc subjected to non-uniform temperature increases. The expressions are optimized with respect to the numerical operations required for the computation of K and p, and they are valid for special cases of material properties and thermal loading.     

Robust design of server capability in M/M/1 queues with both partly random arrival and service rates

In this paper we consider a robust design of controllable factors related to the server capability in M/M/1 queues where both arrival and service rates are assumed to be partly random. The performance of an individual queue is measured in terms of the random traffic intensity parameter defined as the ratio of the arrival rate to the service rate where both rates are functions of associated characteristics of an individual queue and a random error. We utilize the empirical Bayes estimator of the traffic intensity parameter and employ a Monte-Carlo simulation to find the optimal levels of server characteristics with respect to mean squared error. An example is given to illustrate how the proposed procedures can be applied to the robust design of a transmission line.Scope and purposeRobust design is an important issue and has been extensively applied to both product and manufacturing process design so that the resulting quality can consistently satisfy customers under the variation of some uncontrollable factors. We apply this concept to design server capability in a queueing system for given arrival rates. In order to reflect random phenomena, we use Bayesian approach to estimate parameters in the given queueing model. We expect that the resulting robust design procedure can be effectively utilized for budgeting server levels of various queueing systems.