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Spanning subgraph is necessary for the communication in networks. For example, the malfunctioning of one or more nodes in a network in general affects both the global and the local properties of the remaining nodes, because it makes some edges unusable and destroys the connectivity of the system. In this study, we focus on the characters of a network to be fractional-r-factors, fractional (r, k)-extendable...
Bundle adjustment is an effective mean to improve the precision of 3D reconstruction. A fast adjustment algorithm is provided based on the theory of one by one parameter estimation. The time complexity and space complexity of algorithm we provided and classical bundle adjustment algorithm are comparatively analysised. Both simulated and real experiments show that the algorithm we provided can achieve...
K-Means algorithm is one of the most used clustering algorithm for Knowledge Discovery in Data Mining. Seed based K-Means is the integration of a small set of labeled data (called seeds) to the K-Means algorithm to improve its performances and overcome its sensitivity to initial centers. These centers are, most of the time, generated at random or they are assumed to be available for each cluster....
After exploring multi-round difference feature of Serpent encryption algorithm and using the method of constructing S-boxes algebraic equations, we put forward Rectangle algebraic attack of 10-round Serpent-256. This method analyzed that 10-round Serpent-256 needed 2 × 2144 × 210 = 2155 pairs of selective plaintexts, 2155 times of 10-round encryption and 2155 times of 10-round decipher, as well as...
We consider the problem of recovering a signal/image (x) with a k-sparse representation, from hybrid (complex and real), noiseless linear samples (y) using a mixture of complex-valued sparse and real-valued dense projections within a single matrix. The proposed Hybrid Compressed Sensing (HCS) employs the complex-sparse part of the projection matrix to divide the n-dimensional signal (x) into subsets...
In this paper, a class of quasi-orthogonal space-time block codes (Q-STBC) is proposed for systems with 2 antennas and 3 time slots, where the orthogonal Alamouti code can not be applied due to the “odd symbol” problem inherited in the 3GPP frame structure. The proposed codes can achieve rate one and full diversity with lower complexity maximum likelihood detection. The design takes into consideration...
This paper presents an efficient multiuser Multiple Input Multiple Output (MU-MIMO) detection algorithm. It introduces Cholesky Decomposition (CLD) and deploys Successive Interference Cancellation (SIC) detection. This study reveals that the proposed algorithm delivers equivalent performance to the QR Decomposition (QRD) based detection algorithm, with adequately lower complexity. As well, the CLD...
Based on the concept of hybrid shift-invariant spaces, we develop a distributed protocol for the reconstruction of time-varying physical fields in wireless sensor networks. The localized nature of these spaces allows for a clustered network architecture that leads to low communication overhead. Capitalizing on the sparsity of the reconstruction matrix, we propose an iterative reconstruction algorithm...
This paper presents a novel Radial Basis Function (RBF) iterative method for nonlinear electromagnetic problems by introducing RBF collocation technique into Newton iteration. This method based firstly on transforming electromagnetic partial differential equations into high order coupled equations on many advantages of RBF collocation technique, then get numerical results from a novel self-optimized...
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