Minimal paths (MPs) play an important role in network reliability evaluation. In this paper, we report an efficient recursive algorithm for finding all MPs in two-terminal networks, which consist of a source node and ...
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Minimal paths (MPs) play an important role in network reliability evaluation. In this paper, we report an efficient recursive algorithm for finding all MPs in two-terminal networks, which consist of a source node and a sink node. A linked path structure indexed by nodes is introduced, which accepts both directed and undirected form of networks. The distance between each node and the sink node is defined, and a simple recursive algorithm is presented for labeling the distance for each node. Based on the distance between each node and the sink node, additional conditions for backtracking are incorporated to reduce the number of search branches. With the newly introduced linked node structure, the distances between each node and the sink node, and the additional backtracking conditions, an improved backtracking algorithm for searching for all MPs is developed. In addition, the proposed algorithm can be adapted to search for all minimal paths for each source-sink pair in networks consisting of multiple source nodes and/or multiple sink nodes. Through computational experiments, it is demonstrated that the proposed algorithm is more efficient than existing algorithms when the network size is not too small. The proposed algorithm becomes more advantageous as the size of the network grows. (C) 2016 Elsevier Ltd. All rights reserved.
The optimal reduced-order estimation problem in which the plant model depends on parameters, which are known at the time of operation, is considered. Such cases occur when the parameters are either measurable or their...
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The optimal reduced-order estimation problem in which the plant model depends on parameters, which are known at the time of operation, is considered. Such cases occur when the parameters are either measurable or their changing values are known in advance, A method for approximation of the updated estimator, without complete re-solution of the problem, is given. A similar approach is used to develop a new algorithm for the numerical solution of the nominal reduced-order estimation problem.
This paper presents a novel fully recursive method, a direct differentiation based approach, which facilitates first-order sensitivity analysis in optimal design problems involving multibody dynamic systems. A state s...
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This paper presents a novel fully recursive method, a direct differentiation based approach, which facilitates first-order sensitivity analysis in optimal design problems involving multibody dynamic systems. A state space O(n) dynamic analysis algorithm based on a velocity space projection method, as promoted by Kane [18], forms the foundation of the underlying formulation. This algorithm can significantly reduce the massive number of mathematical and associated computational operations involved in explicitly generating and solving the sensitivity equations. This benefit is particularly evident for systems involving a combination of many state variables and design parameters. The development presented in this paper focuses on chain systems to illustrate the recursive nature of the algorithm. The computational efficiency and solution accuracy of the presented algorithm are investigated through the procedures application to the simulation and design sensitivity determination of spatial chain systems involving 2, 4, 6, ..., 24 degrees of freedom, as well as a simple planar double pendulum.
This paper addresses an optimization model for assembly line-balancing problem in order to improve the line balance of a production line under a human-centric and dynamic apparel assembly process. As the variance of o...
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This paper addresses an optimization model for assembly line-balancing problem in order to improve the line balance of a production line under a human-centric and dynamic apparel assembly process. As the variance of operator efficiency is vital to line imbalance in labor intensive industry, an approach is proposed to balance production line through optimal operator allocation with the consideration of operator efficiency. Two recursive algorithms are developed to generate all feasible solutions for operator allocation. Three objectives, namely, the lowest standard deviation of operation efficiency, the highest production line efficiency and the least total operation efficiency waste, are devised to find out the optimal solution of operator allocation. The method in this paper improves the flexibility of the operator allocation on different sizes of data set of operations and operators, and enhances the efficiency of searching for the optimal solution of big size data set. The results of experiments are reported. The performance comparison demonstrates that the proposed optimization method outperforms the industry practice. (c) 2006 Elsevier Ltd. All rights reserved.
In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The r...
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In this paper, the authors consider an adaptive recursive algorithm by selecting an adaptive sequence for computing M-estimators in multivariate linear regression models. Its asymptotic property is investigated. The recursive algorithm given by Miao and Wu （1996） is modified accordingly. Simu- lation studies of the Mgorithm is also provided. In addition, the Newton-Raphson iterative algorithm is considered for the purpose of comparison.
The quadratic approximation is a three dimensional analogue of the two dimensional Padé approximation. A determinantal expression for the polynomial coefficients of the quadratic approximation is given. A recursi...
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The quadratic approximation is a three dimensional analogue of the two dimensional Padé approximation. A determinantal expression for the polynomial coefficients of the quadratic approximation is given. A recursive algorithm for the construction of these coefficients is derived. The algorithm constructs a table of quadratic approximations analogous to the Padé table of rational approximations.
This work focuses on numerical algorithms for approximating the ergodic means for suitable functions of solutions to stochastic differential equations with Markov regime switching. Our main effort is devoted to obtain...
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This work focuses on numerical algorithms for approximating the ergodic means for suitable functions of solutions to stochastic differential equations with Markov regime switching. Our main effort is devoted to obtaining the convergence and rates of convergence of the approximation algorithms. The study is carried out by obtaining laws of large numbers and laws of iterated logarithms for numerical approximation to long-run averages of suitable functions of solutions to switching diffusions. (C) 2015 Elsevier B.V. All rights reserved.
A fast recursive algorithm for determining the Gaussian filtered mean line was deduced using the central limit theorem and an approximation method. This recursive algorithm uses a small number of multiplications per l...
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A fast recursive algorithm for determining the Gaussian filtered mean line was deduced using the central limit theorem and an approximation method. This recursive algorithm uses a small number of multiplications per loop and otherwise such simple computer operations as addition and subtraction, and therefore, can achieve a very high computational speed. Special cases are also presented in which the relatively inefficient multiplication operation in the computer can be replaced by the efficient digit shifting operation, and the filtering computational efficiency is enhanced further. High-order algorithms are proposed for practical use to improve filtering accuracy. The "forward filtering" and "backward filtering" implementation of the recursive algorithm results in zero phase distortion of the filtered mean Line. A new relationship between the Gaussian filtering method and the classical 2RC filtering method is also established using this algorithm. Published by Elsevier Science Inc.
A general, recursive algorithm is presented for computing the expected Fisher information matrix for state-space model parameters. Simulation results are featured where known Fisher information matrices corresponding ...
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A general, recursive algorithm is presented for computing the expected Fisher information matrix for state-space model parameters. Simulation results are featured where known Fisher information matrices corresponding to simple state-space models are estimated using both observed and expected information matrices. The accuracy of the two approaches is compared.
The discrete cosine transform (DCT) has been successfully used for a wide range of applications in digital signal processing. While there are efficient algorithms for implementing the DCT, its use becomes difficult in...
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The discrete cosine transform (DCT) has been successfully used for a wide range of applications in digital signal processing. While there are efficient algorithms for implementing the DCT, its use becomes difficult in the sliding transform scenario where the transform window is shifted one sample at a time and the transform process is repeated. In this paper, a new two-dimensional sliding DCT (2-D SDCT) algorithm is proposed for fast implementation of the DCT on 2-D sliding windows. In the proposed algorithm, the DCT coefficients of the shifted window are computed by exploiting the recursive relationship between 2-D DCT outputs of three successive windows. The theoretical analysis shows that the computational requirement of the proposed 2-D SDCT algorithm is the lowest among existing 2-D DCT algorithms. Moreover, the proposed algorithm enables independent updating of each DCT coefficient. (C) 2016 Elsevier Inc. All rights reserved.
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