With the explosive growth of online alternative objects, the availability of a credible rating system could play a valuable role for users who are evaluating and/or choosing items. Due to the existence of spammers, ma...
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With the explosive growth of online alternative objects, the availability of a credible rating system could play a valuable role for users who are evaluating and/or choosing items. Due to the existence of spammers, many methods have been proposed that employ a reputation-based mechanism in the last few years. However, these methods only consider spammers' behaviours but neglect the effect of thorny objects, which are difficult to evaluate because of their intrinsic uncertainty and complexity with respect to the problem context, knowledge gaps, and various user criteria. To solve this problem, we propose a new reputation iterative algorithm based on Z-statistics (ZS), which eliminates the effect of thorny objects and strengthens the ability to deal with spammers. In this article, the proposed method makes effectiveness comparisons with other typical methods using a rating example and a simulated rating system, and presents additional effectiveness and complexity analyses of these results. Finally, the experimental results also demonstrate that the ZS algorithm outperforms other methods in simultaneously dealing with the effects of spammers and thorny objects.
In this letter, we introduce a fast and computationally efficient iterative algorithm for joint zero diagonalization of a set of complex-valued target matrices. The proposed algorithm is actually a low complexity vers...
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In this letter, we introduce a fast and computationally efficient iterative algorithm for joint zero diagonalization of a set of complex-valued target matrices. The proposed algorithm is actually a low complexity version of FJZD algorithm, it has a computational complexity of O(KN2), where K and N and are the number and dimension of the target matrices respectively. Moreover, the proposed algorithm is superior to FJZD in terms of interference to signal ratio. Simulation results demonstrate the good performance of the proposed algorithm.
First a new system of nonlinear set-valued variational inclusions involving (A, eta)-monotone mappings in Hilbert spaces is introduced and then its solvability is explored. Based on the general resolvent operator meth...
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First a new system of nonlinear set-valued variational inclusions involving (A, eta)-monotone mappings in Hilbert spaces is introduced and then its solvability is explored. Based on the general resolvent operator method associated with (A, eta)-monotone mappings, approximation solvability of this system of nonlinear set-valued variational inclusions is established. The convergence analysis is discussed in detail. The obtained results generalize a number of results on nonlinear variational inclusion systems. (C) 2006 Elsevier Ltd. All rights reserved.
High-accuracy numerical method for uncertainty propagation analysis is a crucial issue in the field of structural reliability design. In this work, a novel iterative algorithm is proposed to study the free vibration o...
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High-accuracy numerical method for uncertainty propagation analysis is a crucial issue in the field of structural reliability design. In this work, a novel iterative algorithm is proposed to study the free vibration of the functionally graded (FG) thin plates with material uncertainties. As a highly accurate approach distinct from the existing non-iterative model, the frequency analysis of FG thin plates can be achieved by updating the lower and upper bounds of natural frequency step by step. Based on the classic plate theory, the governing equations of the FG thin plate resting on an elastic medium are derived and the analytical formulation for the natural frequency is presented. By introducing interval parameters to quantify the material uncertainties, a non-probabilistic model for evaluating the natural frequency response of the embedded FG thin plate is developed. Subsequently, the deduction of the novel iterative algorithm for solving the non-probabilistic model is given based on interval mathematics. The developed model and the proposed iterative algorithm are validated by the Monte Carlo method, and then the detailed parametric studies are carried out to explore the combined influences of material uncertainties, power-law index, and elastic foundation parameters, as well as size parameters on the natural frequency of the FG thin plate. Numerical results can provide useful guidance in the precise design of FG structures.
A general A-P iterative algorithm in a shift-invariant space is presented. We use the algorithm to show reconstruction of signals from weighted samples and also show that the general improved algorithm has better conv...
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A general A-P iterative algorithm in a shift-invariant space is presented. We use the algorithm to show reconstruction of signals from weighted samples and also show that the general improved algorithm has better convergence rate than the existing one. An explicit estimate for a guaranteed rate of convergence is given.
The estimation algorithm developed offers an alternative to standard recursive nonlinear estimators such as the extended Kalman filter and the iterated extended Kalman filter. The algorithm, which is developed from a ...
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The estimation algorithm developed offers an alternative to standard recursive nonlinear estimators such as the extended Kalman filter and the iterated extended Kalman filter. The algorithm, which is developed from a quadratic cost function basis, splits the problem of cost function minimization into a linear first step and a nonlinear second step by defining new first-step states that are nonlinear combinations of the unknown states. Estimates of the first-step states are obtained by minimizing the first-step cost function using a Kalman filter formulation. Estimates of the unknown, or second-step, states are obtained by minimizing the second-step cost function using an iterative Gauss-Newton algorithm. The two-step estimator is shown to be optimal for static problems in which the time variation of the measurement equation can be separated from the unknowns. This method is then generalized by approximating the nonlinearity as a perturbation of the dynamic update, while keeping the measurement cost function the same, In contrast, the extended Kalman filter and the iterated extended Kalman filter linearize the measurement cost function, resulting in suboptimal estimates. Two example applications confirm these analytical results.
Based on a new iterative algorithm, the solvability of a class of nonlinear variational inequalities involving a combination of relaxed monotone operators in a Hilbert space setting is presented. (C) 1999 Elsevier Sci...
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Based on a new iterative algorithm, the solvability of a class of nonlinear variational inequalities involving a combination of relaxed monotone operators in a Hilbert space setting is presented. (C) 1999 Elsevier Science Ltd. All rights reserved.
Computation of grasps with form/force closure is one of the fundamental problems in the study of multifingered grasping and dextrous manipulation. Based on the geometric condition of the closure property, this paper p...
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Computation of grasps with form/force closure is one of the fundamental problems in the study of multifingered grasping and dextrous manipulation. Based on the geometric condition of the closure property, this paper presents a numerical test to quantify bow far a grasp is from losing form/force closure. With the polyhedral approximation of the friction cone, the proposed numerical test can be formulated as a single linear program. An iterative algorithm for computing optimal force-closure grasps, which is implemented by minimizing the proposed numerical test in the grasp configuration space, is also developed. The algorithm is computationally efficient and generally applicable. It can be used for computing form/force-closure grasps on 3-D objects with curved surfaces, and with any number of contact points. Simulation examples are given to show the effectiveness and computational efficiency of the proposed algorithm.
In this paper a globally convergent Lagrange and barrier function iterative algorithm is proposed for approximating a solution of the traveling salesman problem. The algorithm employs an entropy-type barrier function ...
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In this paper a globally convergent Lagrange and barrier function iterative algorithm is proposed for approximating a solution of the traveling salesman problem. The algorithm employs an entropy-type barrier function to deal with nonnegativity constraints and Lagrange multipliers to handle linear equality constraints, and attempts to produce a solution of high quality by generating a minimum point of a barrier problem for a sequence of descending values of the barrier parameter. For any given value of the barrier parameter, the algorithm searches for a minimum point of the barrier problem in a feasible descent direction, which has a desired property that the nonnegativity constraints are always satisfied automatically if the step length is a number between zero and one. At each iteration the feasible descent direction is found by updating Lagrange multipliers with a globally convergent iterative procedure. For any given value of the barrier parameter, the algorithm converges to a stationary point of the barrier problem without any condition on the objective function. Theoretical and numerical results show that the algorithm seems more effective and efficient than the softassign algorithm. (C) 2001 Elsevier Science Ltd. All rights reserved.
An iterative Least Square (LS) channel estimation algorithm for MIMO OFDM systems was proposed in this paper. Compared to common LS channel estimation, this algorithm can greatly improve estimation accuracy, and the l...
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An iterative Least Square (LS) channel estimation algorithm for MIMO OFDM systems was proposed in this paper. Compared to common LS channel estimation, this algorithm can greatly improve estimation accuracy, and the low-pass filtering in time domain reduces AWGN and ICI significantly. MIMO OFDM system with this algorithm also works well in mobile situations. Simulation results have shown good MSE performance for this algorithm.
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