Presented is transceiver optimisation for multi-user non-regenerative MIMO relay downlink systems. By taking the channel uncertainties into account, a robust scheme is proposed to minimise the sum mean square error (S...
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Presented is transceiver optimisation for multi-user non-regenerative MIMO relay downlink systems. By taking the channel uncertainties into account, a robust scheme is proposed to minimise the sum mean square error (SMSE) of the system under the power constraints, where the transceiver is obtained by using the Karush-Kuhn-Tucker conditions and realised through an iterative algorithm. Simulation results verify the robustness of the proposed scheme against the estimation errors.
Increased fault level is one of the main concerns connected to the integration of distributed generation (DG) into distribution networks. To accurately calculate fault currents in distribution systems with a high pene...
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Increased fault level is one of the main concerns connected to the integration of distributed generation (DG) into distribution networks. To accurately calculate fault currents in distribution systems with a high penetration of DG, a realistic fault model must be developed that includes the electrical arc existing at the fault point. The results of an assessment of the impact of DG on such arcing faults are presented. The significance of the study is that the fault model includes the electrical arc element, which brings additional non-linear resistance into consideration. Since the arc resistance is a non-linear function of the fault current, the problem of simultaneous fault currents and arc resistance calculation has been tackled using a novel iterative algorithm. In this work, a typical medium voltage distribution network is considered. Results of the simultaneous fault analysis and arc resistance calculation in the IEEE-34 distribution network with a distributed generator are presented and discussed.
In this paper, we propose two iterative algorithms for finding the Hermitian reflexive and skew-Hermitian solutions of the Sylvester matrix equation AX + XB = C, respectively. We prove that the first (second) algorith...
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In this paper, we propose two iterative algorithms for finding the Hermitian reflexive and skew-Hermitian solutions of the Sylvester matrix equation AX + XB = C, respectively. We prove that the first (second) algorithm converges to the Hermitian reflexive (skew-Hermitian) solution for any initial Hermitian reflexive (skew-Hermitian) matrix. Finally, two numerical examples illustrate the theoretical results. (C) 2010 Elsevier Ltd. All rights reserved.
We prove strong convergence theorems for three iterative algorithms which approximate solutions to systems of variational inequalities for mappings of monotone type. All the theorems are set in reflexive Banach spaces...
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We prove strong convergence theorems for three iterative algorithms which approximate solutions to systems of variational inequalities for mappings of monotone type. All the theorems are set in reflexive Banach spaces and take into account possible computational errors.
Some new classes of extended general nonconvex set-valued variational inequalities and the extended general Wiener-Hopf inclusions are introduced. By the projection technique, equivalence between the extended general ...
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Some new classes of extended general nonconvex set-valued variational inequalities and the extended general Wiener-Hopf inclusions are introduced. By the projection technique, equivalence between the extended general nonconvex set-valued variational inequalities and the fixed point problems as well as the extended general nonconvex Wiener-Hopf inclusions is proved. Then by using this equivalent formulation, we discuss the existence of solutions of the extended general nonconvex set-valued variational inequalities and construct some new perturbed finite step projection iterative algorithms with mixed errors for approximating the solutions of the extended general nonconvex set-valued variational inequalities. We also verify that the approximate solutions obtained by our algorithms converge to the solutions of the extended general nonconvex set-valued variational inequalities. The results presented in this paper extend and improve some known results from the literature. (C) 2010 Elsevier Ltd. All rights reserved.
A matrix P is called a symmetric orthogonal matrix if P = P-T = P-1. A matrix X is said to be a generalized bisymmetric with respect to P, if X = X-T = PXP. It is obvious that every symmetric matrix is a generalized b...
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A matrix P is called a symmetric orthogonal matrix if P = P-T = P-1. A matrix X is said to be a generalized bisymmetric with respect to P, if X = X-T = PXP. It is obvious that every symmetric matrix is a generalized bisymmetric matrix with respect to I (identity matrix). In this article, we establish two iterative algorithms for solving the system of generalized Sylvester matrix equations A(1)YB(1) + A(2)YB(2) + ... + A(l)YB(l) = M, C1YD1 + C2YD2 + ... + ClYDl = N, (including the Sylvester and Lyapunov matrix equations as special cases) over the generalized bisymmetric and skew-symmetric matrices, respectively. When this system is consistent over the generalized bisymmetric (skew-symmetric) matrix Y, firstly it is demonstrated that the first (second) algorithm can obtain a generalized bisymmetric (skew-symmetric) solution for any initial generalized bisymmetric (skew-symmetric) matrix. Secondly, by the first (second) algorithm, we can obtain the least Frobenius norm generalized bisymmetric (skew-symmetric) solution for special initial generalized bisymmetric (skew-symmetric) matrices. Moreover, it is shown that the optimal approximate generalized bisymmetric (skew-symmetric) solution of this system for a given generalized bisymmetric (skew-symmetric) matrix (Y) over cap can be derived by finding the least Frobenius norm generalized bisymmetric (skew-symmetric) solution of a new system of generalized Sylvester matrix equations. Finally, the iterative methods are tested with some numerical examples.
An unavoidable problem of most existing skeletonization algorithms for handwriting images is the production of undesired artifacts or pattern distortions. This paper presents a method of identifying these unreliable s...
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An unavoidable problem of most existing skeletonization algorithms for handwriting images is the production of undesired artifacts or pattern distortions. This paper presents a method of identifying these unreliable segments to improve the skeletons of handwriting images. In this method, a novel feature called iteration time is exploited, by which each unreliable segment can be treated as a set of points with exceptional iteration times. First, the iteration time of each skeleton point is calculated, and an undirected graph is built from the skeleton whose edges are weighted by defining a distance measurement between each pair of connected nodes based on iteration time. Then the set of unreliable segments is achieved by a graph clustering algorithm with an effective clustering quality function. Finally, the probability of two jointed reliable segments belonging to a continuous pair is estimated by a best-matched method, and a cubic B-spline interpolation is applied to reconstruct unreliable parts of the skeleton. Experimental results show that the proposed method can detect unreliable segments effectively and produce a skeleton that is closer to the original writing trajectory.
An explicit hierarchical fixed point algorithm is introduced to solve monotone variational inequalities, which are governed by a pair of nonexpansive mappings, one of which is used to define the governing operator and...
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An explicit hierarchical fixed point algorithm is introduced to solve monotone variational inequalities, which are governed by a pair of nonexpansive mappings, one of which is used to define the governing operator and the other to define the feasible set. These kinds of variational inequalities include monotone inclusions and convex optimization problems to be solved over the fixed point sets of nonexpansive mappings. Strong convergence of the algorithm is proved under different circumstances of parameter selections. Applications in hierarchical minimization problems are also included.
Reproducibility is essential to reliable scientific discovery in high-throughput experiments. In this work we propose a unified approach to measure the reproducibility of findings identified from replicate experiments...
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Reproducibility is essential to reliable scientific discovery in high-throughput experiments. In this work we propose a unified approach to measure the reproducibility of findings identified from replicate experiments and identify putative discoveries using reproducibility. Unlike the usual scalar measures of reproducibility, our approach creates a curve, which quantitatively assesses when the findings are no longer consistent across replicates. Our curve is fitted by a copula mixture model, from which we derive a quantitative reproducibility score, which we call the "irreproducible discovery rate" (IDR) analogous to the FDR. This score can be computed at each set of paired replicate ranks and permits the principled setting of thresholds both for assessing reproducibility and combining replicates. Since our approach permits an arbitrary scale for each replicate, it provides useful descriptive measures in a wide variety of situations to be explored. We study the performance of the algorithm using simulations and give a heuristic analysis of its theoretical properties. We demonstrate the effectiveness of our method in a ChIP-seq experiment.
Based on the analysis of the feature of cognitive radio (CR) networks, we build a relevant interference model. Cognitive users should particularly consider the problem of interference with licensed users and satisfy t...
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Based on the analysis of the feature of cognitive radio (CR) networks, we build a relevant interference model. Cognitive users should particularly consider the problem of interference with licensed users and satisfy the signal-to-interference-plus-noise ratio (SINR) requirement at the same time. We propose a new iterative algorithm using the game theory in this paper. We consider not only the SINR requirement as other game algorithms but also the influence of power threshold. The variable power limit is the characteristic of CR. We prove the convergence of the algorithm and the existence of Nash equilibrium. According to different power thresholds, we give an approach for solving the problem of coexistence between licensed user and cognitive user in a cognitive system. The algorithm has the advantage that it can be distributively implemented, and the method converges relatively fast. Numerical results are presented to show that the proposed approach has better antinoise effect and capacity.
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