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重调和方程的梯度恢复型后验误差估计
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作者 刘克光 王成 于亚萍 《唐山学院学报》 2007年第2期1-2,17,共3页
文章给出了第一类重调和方程Ciarlet-Raviart混合变分形式下的梯度恢复型后验误差估计;通过引入加权Cle′ment插值,改进了ZZ梯度恢复法,给出并从理论上证明了后验误差估计的上、下界。
关键词 第一类重调和方程 后验误差估计 梯度恢复法 加权Cle’ment括值
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导弹再入段小弹道倾角攻击问题中的最优控制
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作者 柴斌 佟斓 《战术导弹控制技术》 2011年第2期1-6,共6页
选取再入大气层导弹小弹道倾角攻击目标为研究内容,根据极大值原理。研究了一类在控制有约束、末端时间不固定、末端部分状态变量有约束的条件下,满足某一最优性能指标的要求,达到最优控制目的的问题。首先,建立了导弹再入段纵向平... 选取再入大气层导弹小弹道倾角攻击目标为研究内容,根据极大值原理。研究了一类在控制有约束、末端时间不固定、末端部分状态变量有约束的条件下,满足某一最优性能指标的要求,达到最优控制目的的问题。首先,建立了导弹再入段纵向平面的弹道模型。其次,利用极大值原理.将弹道模型最优控制方程转换为微分方程两点边值问题。最后,针对弹道倾角最小这一要求,综合考虑末端速度及末端时刻,基于序列恢复一梯度法进行了算法改进,并设定参数进行了仿真计算.最终验证了改进算法的科学性和有效性。 展开更多
关键词 导弹再入段攻击 极大值原理 小弹道倾角 序列恢复-梯度 仿真计算
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Gradient based restoration of coal mine images obtained by underground wireless transmissions 被引量:2
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作者 Lu Zhaolin Qian Jiansheng Li Leida 《Mining Science and Technology》 EI CAS 2011年第6期809-813,共5页
Curvature-driven diffusion (CDD) principles were used to develop a novel gradient based image restora- tion algorithm. The algorithm fills in blocks of missing data in a wireless image after transmission through the n... Curvature-driven diffusion (CDD) principles were used to develop a novel gradient based image restora- tion algorithm. The algorithm fills in blocks of missing data in a wireless image after transmission through the network. When images are transmitted over fading channels, especially in the severe circum- stances of a coal mine, blocks of the image may be destroyed by the effects of noise. Instead of using com- mon retransmission query protocols the lost data is reconstructed by using the adaptive curvature-driven diffusion (ACDD) image restoration algorithm in the gradient domain of the destroyed image. Missing blocks are restored by the method in two steps: In step one, the missing blocks are filled in the gradient domain by the ACDD algorithm; in step two, and the image is reconstructed from the reformed gradients by solving a Poisson equation. The proposed method eliminates the staircase effect and accelerates the convergence rate. This is demonstrated by experimental results. 展开更多
关键词 Image restoration Curvature-driven diffusion Gradient domain Wireless image transmission Poisson equation
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Study on Recovering the Earth's Potential Field Based on GOCE Gradiometry
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作者 SHEN Wenbin LI Jin LI Jiancheng WANG Zhengtao NING Jinsheng CHAO Dingbo 《Geo-Spatial Information Science》 2008年第4期273-278,共6页
Given the second radial derivative Vrr(P) |δs of the Earth's gravitational potential V(P) on the surface δS corresponding to the satellite altitude, by using the fictitious compress recovery method, a fictitio... Given the second radial derivative Vrr(P) |δs of the Earth's gravitational potential V(P) on the surface δS corresponding to the satellite altitude, by using the fictitious compress recovery method, a fictitious regular harmonic field rrVrr(P)^* and a fictitious second radial gradient field V:(P) in the domain outside an inner sphere Ki can be determined, which coincides with the real field V(P) in the domain outside the Earth. Vrr^*(P)could be further expressed as a uniformly convergent expansion series in the domain outside the inner sphere, because rrV(P)^* could be expressed as a uniformly convergent spherical harmonic expansion series due to its regularity and harmony in that domain. In another aspect, the fictitious field V^*(P) defined in the domain outside the inner sphere, which coincides with the real field V(P) in the domain outside the Earth, could be also expressed as a spherical harmonic expansion series. Then, the harmonic coefficients contained in the series expressing V^*(P) can be determined, and consequently the real field V(P) is recovered. Preliminary simulation calculations show that the second radial gradient field Vrr(P) could be recovered based only on the second radial derivative V(P)|δs given on the satellite boundary. Concerning the final recovery of the potential field V(P) based only on the boundary value Vrr (P)|δs, the simulation tests are still in process. 展开更多
关键词 GOCE gradiometry second radial gradients second radial gradient field recovery potential field recovery
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