The Internet traffic analysis is important to network management, and extracting the baseline traffic patterns is especially helpful for some significant network applications. In this paper, we study on the baseline p...
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The Internet traffic analysis is important to network management, and extracting the baseline traffic patterns is especially helpful for some significant network applications. In this paper, we study on the baseline problem of the traffic matrix satisfying a refined traffic matrix decomposition model, since this model extends the assumption of the baseline traffic component to characterize its smoothness, and is more realistic than the existing traffic matrix models. We develop a novel baseline scheme, named Stable Principal Component Pursuit with Time-Frequency Constraints (SPCP-TFC), which extends the Stable Principal Component Pursuit (SPCP) by applying new time-frequency constraints. Then we design an efficient numerical algorithm for SPCP-TFC. At last, we evaluate this baseline scheme through simulations, and show it has superior performance than the existing baseline schemes RBL and PCA. (C) 2014 Elsevier GmbH. All rights reserved.
作者：
Lane, R. O.QinetiQ
Malvern Technol Ctr Malvern WR14 3PS Worcs England
Super-resolution of signals and images can improve the automatic detection and recognition of objects of interest. However, the uncertainty associated with this process is not often taken into consideration. This is i...
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Super-resolution of signals and images can improve the automatic detection and recognition of objects of interest. However, the uncertainty associated with this process is not often taken into consideration. This is important because the processing of noisy signals can result in spurious estimates of the scene content. This study reviews a variety of super-resolution techniques and presents two non-parametric Bayesian super-resolution algorithms that not only take uncertainty into account, but also retain knowledge about the output uncertainty in the form of a full probability distribution. One of the two Bayesian techniques is based on an analytical calculation re-interpreted as super-resolution, and the other is a novel numerical algorithm. Although the algorithms are presented as stand-alone techniques for image analysis, such Bayesian super-resolution algorithms can increase automatic target recognition performance over standard super-resolution.
Computation of an ARMA covariance function is a common ingredient in analysis and synthesis of various problems in stochastic control, estimation and signal processing. In this paper, we present an algorithm based on ...
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Computation of an ARMA covariance function is a common ingredient in analysis and synthesis of various problems in stochastic control, estimation and signal processing. In this paper, we present an algorithm based on simple polynomial calculations. Compared to alternative strategies, its computational load increases slowly with the order of the process. Further, it shows good numerical robustness and applies to multivariable ARMA processes, even with complex-valued coefficients.
Chi square distribution is a continuous probability distribution primarily used in hypothesis testing, contingency analysis, and construction of confidence limits in inferential statistics but not necessarily in the m...
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Chi square distribution is a continuous probability distribution primarily used in hypothesis testing, contingency analysis, and construction of confidence limits in inferential statistics but not necessarily in the modeling of real-life phenomena. The closed-form expression for the quantile function (QF) of Chi square is not available because the cumulative distribution function cannot be transformed to yield the QF and consequently places limitations on the use of the QF. Researchers have over the years proposed approximations that improve over time in terms of speed, computational efficiency, and precision, and so on. However, most of the available closed-form expressions (quantile approximation) fail at the extreme tails of the distribution. This paper used the Quantile mechanics approach to obtain second-order nonlinear ordinary differential equations whose solutions using the power series method yielded initial approximates in form of series for different values of the degrees of freedom. The initial approximate varies with the exact (R software) values which serve as the reference and the error between them was minimized by the natural cubic spline interpolation. The final approximates are correct up to an average of 8 decimal places, have small error, and is closer to the exact when compared with some other results from other researchers. The upper tail of the distribution was considered and excellent results were obtained which is a major improvement over the existing results in the literature. The approach used in this work is a hybrid of series expansions and numerical algorithms. Computer codes can be written for the application.
A Crank-Nicolson-type finite-difference scheme is proposed and analyzed for a nonlinear partial integro-differential equation arising from viscoelasticity. The time derivative is approximated by the Crank-Nicolson sch...
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A Crank-Nicolson-type finite-difference scheme is proposed and analyzed for a nonlinear partial integro-differential equation arising from viscoelasticity. The time derivative is approximated by the Crank-Nicolson scheme and the Riemann-Liouville fractional integral term is treated by means of the trapezoidal convolution quadrature rule. To construct a fully discrete difference scheme, the standard centered difference formula is utilized to approximate the second-order spatial derivative and the Galerkin method based on piecewise linear test functions is used to discrete the nonlinear convection term. Theoretical results of stability and convergence are derived using the non-negative character of the real quadratic form associated with the convolution quadrature, and combining with the discrete Gronwall inequality. Besides, a fixed point iterative numerical algorithm, which fills the gap that the existed numerical schemes have only theoretical analysis but no numerical results, is presented. numerical results show the efficiency and feasibility of our scheme, and the orders of convergence are in good agreement with the theoretical results.
The sector stability theorem is an intuitive condition for the stability of feedback loops that unifies many lines of research including robust control and the theory of passive and dissipative systems. Applying this ...
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The sector stability theorem is an intuitive condition for the stability of feedback loops that unifies many lines of research including robust control and the theory of passive and dissipative systems. Applying this theorem typically requires checking or enforcing sector bounds on linear time-invariant systems. This article discusses practical and efficient numerical methods for performing these tasks. We derive a frequency-domain test for sector boundedness and use it to developO(n(3))numerical algorithms for computing the relative or directional indices of sector bounds. We also discuss how such algorithms can be combined with nonsmooth optimization techniques to enforce sector bounds while designing and tuning controllers. Several application examples illustrate the potential of these tools and techniques.
We study an optimal quantum measurement for generalized quantum state discrimination problems, which include the problem of finding an optimal measurement maximizing the average success probability with and without a ...
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We study an optimal quantum measurement for generalized quantum state discrimination problems, which include the problem of finding an optimal measurement maximizing the average success probability with and without a fixed rate of inconclusive results and the problem of finding an optimal measurement in the Neyman-Pearson strategy. We show that for any generalized quantum state discrimination problem, there is a corresponding minimum error discrimination problem sharing the same optimal measurement. We propose an approach in which the optimal measurement is obtained by solving the corresponding minimum error discrimination problem, and clarify the relationship between optimal solutions to the original and the corresponding problems, with which one can obtain an optimal solution to the original problem in some cases. Moreover, as an example of application of our approach, we present an algorithm for numerically obtaining optimal solutions to generalized quantum state discrimination problems.
We revisit the method of characteristics for shock wave solutions to nonlinear hyperbolic problems and we propose a novel numerical algorithm-the convex hull algorithm (CHA) which allows us to compute both entropy dis...
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We revisit the method of characteristics for shock wave solutions to nonlinear hyperbolic problems and we propose a novel numerical algorithm-the convex hull algorithm (CHA) which allows us to compute both entropy dissipative solutions (satisfying all entropy inequalities) and entropy conservative (or multi-valued) solutions. From the multi-valued solutions determined by the method of characteristics, our algorithm "extracts" the entropy dissipative solutions, even after the formation of shocks. It applies to both convex and non-convex flux/Hamiltonians. We demonstrate the relevance of the proposed method with a variety of numerical tests, including conservation laws in one or two spatial dimensions and problem arising in fluid dynamics. (C) 2015 Elsevier Inc. All rights reserved.
numerical methods are used to find exact solution for the nonlinear differential equations. In the last decades Iterative methods have been used for solving fractional differential equations. In this paper, the Homoto...
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numerical methods are used to find exact solution for the nonlinear differential equations. In the last decades Iterative methods have been used for solving fractional differential equations. In this paper, the Homotopy perturbation method has been successively applied for finding approximate analytical solutions of the fractional nonlinear Klein-Cordon equation can be used as numerical algorithm. The behavior of solutions and the effects of different values of fractional order a are shown graphically. Some examples are given to show ability of the method for solving the fractional nonlinear equation. Crown Copyright (C) 2010 Published by Elsevier B.V. All rights reserved.
This paper considers the optimal rejuvenation policy problem for software systems performing real-time tasks. Due to software aging, the system performance deteriorates with time eventually leading to the system crash...
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This paper considers the optimal rejuvenation policy problem for software systems performing real-time tasks. Due to software aging, the system performance deteriorates with time eventually leading to the system crash, which can be catastrophic for critical applications. To prevent the system crash or minimize its occurrence probability, software rejuvenation has been widely adopted for counteracting the software aging effect but at the cost of extra system overhead and downtime. We derive the optimal state-based rejuvenation policy minimizing the total expected mission cost for software aging systems subject to multiple performance degradation states. The solution encompasses an event transition-based numerical method that assesses the total expected mission cost of a real-time task, covering penalty cost from the mission failure, operation cost of running the mission software and the expected rejuvenation cost. The proposed cost evaluation model can accommodate arbitrary types of state transition time distributions. The suggested model also allows simultaneous evaluations of other system performance metrics including the probability of the successful task completion (i.e., mission reliability) and conditional expected mission completion time given a successful mission task. Examples are presented to demonstrate the proposed methodology and optimizations. Effects of different parameters on the rejuvenation optimization solution are also investigated.
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