Institution
National University of Defense Technology
Education•Changsha, China•
About: National University of Defense Technology is a education organization based out in Changsha, China. It is known for research contribution in the topics: Radar & Synthetic aperture radar. The organization has 39430 authors who have published 40181 publications receiving 358979 citations. The organization is also known as: Guófáng Kēxuéjìshù Dàxué & NUDT.
Topics: Radar, Synthetic aperture radar, Laser, Fiber laser, Radar imaging
Papers published on a yearly basis
Papers
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TL;DR: This paper provides a complete 3D configuration analysis for P3L, which includes the well-known P3P problem as well as several existing analyses as special cases, and proposed linear-formulation-based PnL approaches inspired by their PnP counterparts are proposed.
Abstract: In this paper we deal with the camera pose estimation problem from a set of 2D/3D line correspondences, which is also known as PnL (Perspective-n-Line) problem. We carry out our study by comparing PnL with the well-studied PnP (Perspective-n-Point) problem, and our contributions are three-fold: (1) We provide a complete 3D configuration analysis for P3L, which includes the well-known P3P problem as well as several existing analyses as special cases. (2) By exploring the similarity between PnL and PnP, we propose a new subset-based PnL approach as well as a series of linear-formulation-based PnL approaches inspired by their PnP counterparts. (3) The proposed linear-formulation-based methods can be easily extended to deal with the line and point features simultaneously.
120 citations
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TL;DR: Under the condition of n+/spl kappa/=const, the basic difference between the unscented Kalman filtering for the nonlinear dynamic systems with additive process and measurement noises is that the augmented UKF draws a sigma set only once within a filtering recursion, while the nonaugmented UKF has to redraw a new set of sigma points to incorporate the effect of additive process noise.
Abstract: This paper concerns the unscented Kalman filtering (UKF) for the nonlinear dynamic systems with additive process and measurement noises. It is widely accepted for such a case that the system state needs not to be augmented with noise vectors and the resultant nonaugmented UKF yields similar, if not the same, results to the augmented UKF. In this letter, we find that under the condition of n+/spl kappa/=const, the basic difference between them is that the augmented UKF draws a sigma set only once within a filtering recursion, while the nonaugmented UKF has to redraw a new set of sigma points to incorporate the effect of additive process noise. This difference generally favors the augmented UKF in that the odd-order moment information is partly captured by the nonlinearly transformed sigma points and propagated throughout the recursion. The simulation results agree well with the analyses.
119 citations
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18 Dec 2010TL;DR: Experimental evaluation validates that the proposed kernel fusion method could reduce energy consumption without performance loss for several typical kernels and effective method to reduce the usage of shared memory and coordinate the thread space of the kernels to be fused is proposed.
Abstract: As one of the most popular accelerators, Graphics Processing Unit (GPU) has demonstrated high computing power in several application fields. On the other hand, GPU also produces high power consumption and has been one of the most largest power consumers in desktop and supercomputer systems. However, software power optimization method targeted for GPU has not been well studied. In this work, we propose kernel fusion method to reduce energy consumption and improve power efficiency on GPU architecture. Through fusing two or more independent kernels, kernel fusion method achieves higher utilization and much more balanced demand for hardware resources, which provides much more potential for power optimization, such as dynamic voltage and frequency scaling (DVFS). Basing on the CUDA programming model, this paper also gives several different fusion methods targeted for different situations. In order to make judicious fusion strategy, we deduce the process of fusing multiple independent kernels as a dynamic programming problem, which could be well solved with many existing tools and be simply embedded into compiler or runtime system. To reduce the overhead introduced by kernel fusion, we also propose effective method to reduce the usage of shared memory and coordinate the thread space of the kernels to be fused. Detailed experimental evaluation validates that the proposed kernel fusion method could reduce energy consumption without performance loss for several typical kernels.
119 citations
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TL;DR: In this paper, the effects of rare-earth elements substitution on microstructural and electromagnetic properties were analyzed and the matching thickness and the reflection loss (RL) of one-layer ferrite absorber were calculated.
119 citations
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10 Apr 2011
TL;DR: This paper presents ETCH, Efficient Channel Hopping based MAC-layer protocols for communication rendezvous in DSA networks and proposes two protocols, SYNC-ETCH and ASYNC-etCH, which achieve better time-to-rendezvous and throughput compared to previous work.
Abstract: In a dynamic spectrum access (DSA) network, communication rendezvous is the first step for two secondary users to be able to communicate with each other. In this step, the pair of secondary users meet on the same channel, over which they negotiate on the communication parameters, to establish the communication link. This paper presents ETCH, Efficient Channel Hopping based MAC-layer protocols for communication rendezvous in DSA networks. We propose two protocols, SYNC-ETCH and ASYNC-ETCH. Both protocols achieve better time-to-rendezvous and throughput compared to previous work.
118 citations
Authors
Showing all 39659 results
Name | H-index | Papers | Citations |
---|---|---|---|
Rui Zhang | 151 | 2625 | 107917 |
Jian Li | 133 | 2863 | 87131 |
Chi Lin | 125 | 1313 | 102710 |
Wei Xu | 103 | 1492 | 49624 |
Lei Liu | 98 | 2041 | 51163 |
Xiang Li | 97 | 1472 | 42301 |
Chang Liu | 97 | 1099 | 39573 |
Jian Huang | 97 | 1189 | 40362 |
Tao Wang | 97 | 2720 | 55280 |
Wei Liu | 96 | 1538 | 42459 |
Jian Chen | 96 | 1718 | 52917 |
Wei Wang | 95 | 3544 | 59660 |
Peng Li | 95 | 1548 | 45198 |
Jianhong Wu | 93 | 726 | 36427 |
Jianhua Zhang | 92 | 415 | 28085 |