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Uniquely Decomposable Constellation Group-Based Sparse Vector Coding for Short Packet Communications
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作者 Xuewan Zhang Hongyang Chen +3 位作者 Di Zhang Ganyu Qin Battulga Davaasambuu Takuro Sato 《China Communications》 SCIE CSCD 2023年第5期119-134,共16页
Sparse vector coding(SVC)is emerging as a potential technology for short packet communications.To further improve the block error rate(BLER)performance,a uniquely decomposable constellation group-based SVC(UDCG-SVC)is... Sparse vector coding(SVC)is emerging as a potential technology for short packet communications.To further improve the block error rate(BLER)performance,a uniquely decomposable constellation group-based SVC(UDCG-SVC)is proposed in this article.Additionally,in order to achieve an optimal BLER performance of UDCG-SVC,a problem to optimize the coding gain of UDCG-based superimposed constellation is formulated.Given the energy of rotation constellations in UDCG,this problem is solved by converting it into finding the maximized minimum Euclidean distance of the superimposed constellation.Simulation results demonstrate the validness of our derivation.We also find that the proposed UDCGSVC has better BLER performance compared to other SVC schemes,especially under the high order modulation scenarios. 展开更多
关键词 ultra-reliable and low latency communications sparse vector coding uniquely decomposable constellation group constellation rotation short packet communications
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New regularization method and iteratively reweighted algorithm for sparse vector recovery 被引量:1
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作者 Wei ZHU Hui ZHANG Lizhi CHENG 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2020年第1期157-172,共16页
Motivated by the study of regularization for sparse problems,we propose a new regularization method for sparse vector recovery.We derive sufficient conditions on the well-posedness of the new regularization,and design... Motivated by the study of regularization for sparse problems,we propose a new regularization method for sparse vector recovery.We derive sufficient conditions on the well-posedness of the new regularization,and design an iterative algorithm,namely the iteratively reweighted algorithm(IR-algorithm),for efficiently computing the sparse solutions to the proposed regularization model.The convergence of the IR-algorithm and the setting of the regularization parameters are analyzed at length.Finally,we present numerical examples to illustrate the features of the new regularization and algorithm. 展开更多
关键词 regularization method iteratively reweighted algorithm(IR-algorithm) sparse vector recovery
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Stroke-Based Surface Reconstruction
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作者 Jooyoung Hahn Jie Qiu +3 位作者 Eiji Sugisaki Lei Jia Xue-Cheng Tai Hock Soon Seah 《Numerical Mathematics(Theory,Methods and Applications)》 SCIE 2013年第1期297-324,共28页
In this paper,we present a surface reconstruction via 2D strokes and a vector field on the strokes based on a two-step method.In the first step,from sparse strokes drawn by artists and a given vector field on the stro... In this paper,we present a surface reconstruction via 2D strokes and a vector field on the strokes based on a two-step method.In the first step,from sparse strokes drawn by artists and a given vector field on the strokes,we propose a nonlinear vector interpolation combining total variation(TV)and H1 regularization with a curl-free constraint for obtaining a dense vector field.In the second step,a height map is obtained by integrating the dense vector field in the first step.Jump discontinuities in surface and discontinuities of surface gradients can be well reconstructed without any surface distortion.We also provide a fast and efficient algorithm for solving the proposed functionals.Since vectors on the strokes are interpreted as a projection of surface gradients onto the plane,different types of strokes are easily devised to generate geometrically crucial structures such as ridge,valley,jump,bump,and dip on the surface.The stroke types help users to create a surface which they intuitively imagine from 2D strokes.We compare our results with conventional methods via many examples. 展开更多
关键词 Surface reconstruction from a sparse vector field augmented Lagrangian method twostep method curl-free constraint total variation regularization preservation of discontinuities in surface normal vectors
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