The introduction of quaternions in the quantum chemistry framework provides new ideas for solving some of the difficulties encountered in traditional approaches and is expected to expand the scope of quantum chemistry...
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The introduction of quaternions in the quantum chemistry framework provides new ideas for solving some of the difficulties encountered in traditional approaches and is expected to expand the scope of quantum chemistry research. This paper investigates the eigenvalue problem of a Hermitian quaternion matrix by means of the complex representation of a quaternion matrix. This paper also gives an efficient algebraic algorithm for finding the eigenvalues and eigenvectors of a Hermitian quaternion matrix, which requires much less computational time than existing algorithms. This novel algorithm provides an algebraic method for quantum chemistry research and is expected to have potential applications in large-scale molecular structure prediction and reaction mechanism studies.
The identification of misbehaving elements in a distributed system is an important task in many diverse settings that can be represented as graphs;this problem can be cast as the computation of a subset of the graph n...
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The identification of misbehaving elements in a distributed system is an important task in many diverse settings that can be represented as graphs;this problem can be cast as the computation of a subset of the graph nodes by exploiting a pre-determined detection mechanism. In this paper we propose a simple yet accurate algorithm to compute the set of nodes of a graph suspected to be malicious that is based on the so called comparison detection model. In this framework, a node can play the role of the comparator for two of its neighbors and can provide a boolean result based on the actual status of both. The algorithm we propose has low computational complexity and linear space complexity;furthermore, it only requires one parameter to trade accuracy against computational cost. We also show it outperforms the state-of-the-art and performs equally very well on both synthetic and real world graphs.
Many switches and some thresholds occur frequently in most practical contexts of strategic decision making. Generally these two aspects have been studied separately. This study approaches the identification problem in...
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Many switches and some thresholds occur frequently in most practical contexts of strategic decision making. Generally these two aspects have been studied separately. This study approaches the identification problem in a synthetic manner. Several combinations of objectives of decision making, with no clear combination in perspective, render it difficult to measure the dependent variable. A case in point is the concept of consumer loyalty to the products of a firm. Clearly, many independent variables have effects on an array of dependent *** different methods of dealing with the unobservable dependent variable have been examined. In addition, almost all studies postulate that the switches and threshold levels satisfy a predefined probability distribution. The resulting estimates crucially depend on this assumption rather than reflect the nature of the data. By way of contrast, this study develops estimates of these changes without such an assumption. Further, suitable transformations of variables have been developed so that the non-linear regression can be converted into a simple linear regression. The case of 3MIndia was developed to illustrate the application of the proposed methods.
Active reconfigurable intelligent surface (RIS) is a new RIS architecture that can reflect and amplify communication signals. It can provide enhanced performance gain compared to the conventional passive RIS systems t...
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ISBN:
(纸本)9798350344868;9798350344851
Active reconfigurable intelligent surface (RIS) is a new RIS architecture that can reflect and amplify communication signals. It can provide enhanced performance gain compared to the conventional passive RIS systems that can only reflect the signals. On the other hand, the design problem of active RIS-aided systems is more challenging than the passive RIS-aided systems and its efficient algorithms are less studied. In this paper, we consider the sum rate maximization problem in the multiuser massive multiple-input single-output (MISO) downlink with the aid of a large-scale active RIS. Existing approaches for handling this problem usually resort to general optimization solvers and can be computationally prohibitive. We propose an efficient block successive upper bound minimization (BSUM) method, of which each step has a (semi) closed-form update. Thus, the proposed algorithm has an attractive low per-iteration complexity. By simulation, our proposed algorithm consumes much less computation than the existing approaches. In particular, when the MIMO and/or RIS sizes are large, our proposed algorithm can be orders-of-magnitude faster than existing approaches.
In this paper, we investigate a nonconvex robust fractional quadratically constrained quadratic problem (Robust Fractional QCQP), which has a wide application to the worst-cast resource allocation optimization in wire...
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In this paper, we investigate a nonconvex robust fractional quadratically constrained quadratic problem (Robust Fractional QCQP), which has a wide application to the worst-cast resource allocation optimization in wireless multiuser beamforming systems. The state-of-the-art method is based on semidefinite relaxation (SDR), which possibly returns a high-rank solution and makes it difficult to recover a robustly feasible solution. To overcome this drawback, we propose an efficient algorithm for solving the robust fractional QCQP by employing the constrained concave-convex procedure and the cutting set method. When finding a robustly feasible initial point is nontrivial, we propose an effective method to deal with it. We also develop the parallel implementation of the proposed algorithm to speed up the computation aiming for real-time application scenarios. As a case study, in the second part of the paper we focus on two examples, namely: i) a novel robust nonorthogonal multiple access (NOMA) multiuser beamforming for physical layer security;and ii) the renowned robust signal-to-interference-and-noise ratio (SINR) balancing problem of cognitive radio multiuser beamforming systems. Numerical results are presented to verify the effectiveness of our proposed algorithm compared with the state-of-the-art methods.
The classical chroma subsampling involves downsampling chrominance components (U and V) while maintaining the luminance component (Y). Recently, a study has attempted to change Y for the chroma-subsampling process, an...
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The classical chroma subsampling involves downsampling chrominance components (U and V) while maintaining the luminance component (Y). Recently, a study has attempted to change Y for the chroma-subsampling process, and improved results in the reconstructed image quality are obtained. However, computational complexity remains an issue because the study examines all the candidates in the determined range for minimal pixel distortion for the modified Y;the complexity can be high if the range is large. In this study, we reduced the candidate number to seven at most, which is mathematically optimized. Boundary points for in-the-range red, green, and blue (RGB) values are first decided, followed by the determination of the intervals that concatenate the entire curve (at most seven intervals). Each interval belongs to one of the seven sub-cases of different linear combinations of individual curves. The optimal solution (modified Y) for each sub-case is derived, which is in highly efficient form. Compared with the existing method, the proposed fast method ensures that the image quality is preserved, while the number of search candidates is reduced by 61.30%-69.19% on average, and the computational time of the process is reduced by 31.39%-58.97%, thereby demonstrating an efficient performance.
This paper proposes a computationally efficient algorithm, FBS (Fast Binary Segmentation), for both single and multiple change point detection under high-dimensional setups. As a general technique, it can be widely us...
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This paper proposes a computationally efficient algorithm, FBS (Fast Binary Segmentation), for both single and multiple change point detection under high-dimensional setups. As a general technique, it can be widely used in various change point problems including mean vectors and covariance matrices change point models. Based on various l((s,p))-norm aggregations for the cumulative sum (CUSUM) statistics, the new algorithm can be applied to a wide range of alternative structures including sparse and dense settings as special cases. We present the essence of the new algorithm. The efficiency and accuracy of the new algorithm are justified via comparing it with the other existing techniques. Lastly, a real data application further demonstrates the usefulness of our method.
An efficient algorithm is presented for computing exact system and survival signatures of K-terminal reliability in undirected networks with unreliable edges. K-terminal reliability is defined as the probability that ...
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An efficient algorithm is presented for computing exact system and survival signatures of K-terminal reliability in undirected networks with unreliable edges. K-terminal reliability is defined as the probability that a subset K of the network nodes can communicate with each other. Signatures have several advantages over direct reliability calculation such as enabling certain stochastic comparisons of reliability between competing network topology designs, extremely fast repeat computation of network reliability for different edge reliabilities and computation of network reliability when failures of edges are exchangeable but not independent. Existing methods for computation of signatures for K-terminal network reliability require derivation of cut-sets or path-sets which is only feasible for small networks due to the computational expense. The new algorithm utilises binary decision diagrams, boundary set partition sets and simple array operations to efficiently compute signatures through a factorisation of the network edges. The performance and advantages of the algorithm are demonstrated through application to a set of benchmark networks and a sensor network from an underground mine.
This article is devoted to designing efficient linear finite element algorithm for the fractional Cahn-Hilliard equation, an important and newly proposed phase field model. Combining the advantages of the classic BiCG...
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This article is devoted to designing efficient linear finite element algorithm for the fractional Cahn-Hilliard equation, an important and newly proposed phase field model. Combining the advantages of the classic BiCG algorithm and the Toeplitz-like structure of the coefficient matrix, we develop a fast BiCG(FBiCG) algorithm for the linearized scheme to compute numerically the fractional Cahn-Hilliard equation. Our theoretical analysis and numerical experiments demonstrate that the proposed FBiCG reduces the computation cost and the storage to O(M log M) and O(M), possesses the same convergence rates as Newton's algorithm does in space and time, and preserves the energy dissipation and equality laws. The numerical experiments also demonstrate that the FBiCG is almost mass conserved, recognizes accurately the phase separation by a very clear coarse graining process and the influences of different indices r and s of fractional Laplacian and different coefficients K and a on the width of the interfaces. (C) 2019 Elsevier B.V. All rights reserved.
Sawmills in Thailand demand an automatic approach to correctly detect rubberwood pith. This is a starting point to maximize the yield of slabs. Knowing the pith location at both end faces of a log makes it possible fo...
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Sawmills in Thailand demand an automatic approach to correctly detect rubberwood pith. This is a starting point to maximize the yield of slabs. Knowing the pith location at both end faces of a log makes it possible for a log scaler to turn the log to align both piths parallel to a bandsaw. Then, the likely to defect part, the knot, can be removed. The rest of the log is then cut to produce a set of slabs. In this paper, an algorithm is proposed to accelerate estimating the pith location of rubberwood with lower estimation error from the untreated cross section image captured by a normal camera. The algorithm employs the histogram of oriented gradients and a set of relevant histogram bin indices to reduce the number of line segments to be successively used in a computational intensive group of line intersection part of the algorithm. The results confirm that the execution time of the proposed algorithm is 187 times and the estimation correctness is 2.69 times compared to the formerly proposed method for European species on a set of 35 cross section rubberwood images taken from a realistic sawmill environment.
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