现有大多遥感图像超分辨率方法,无法充分挖掘图像中混合尺度的自相似性信息和跨尺度区域间的关联信息,且忽略了频率域对感知图像高频信息的能力。针对这一问题,本文提出了一种空间自适应及频率融合网络(Spatial Adaptation and Frequenc...现有大多遥感图像超分辨率方法,无法充分挖掘图像中混合尺度的自相似性信息和跨尺度区域间的关联信息,且忽略了频率域对感知图像高频信息的能力。针对这一问题,本文提出了一种空间自适应及频率融合网络(Spatial Adaptation and Frequency Fusion Network,SAF2Net)。SAF2Net首先引入一种混合尺度空间自适应特征调制模块,采用类似于特征金字塔的方式获取不同尺度下的判别特征,丰富多尺度特征的表达能力。随后,设计了一个全局多尺度感受野选择块,挖掘跨尺度区域间的关联特征。在此基础上,引入空间自适应选择块和频率分离选择块,融合空间-频率互补信息以增强局部特征,提高模型对图像高频内容的建模能力。在两个公开遥感图像数据集上进行多组实验,SAF2Net获得的定量评价指标结果均优于其他对比方法。以UCMerced数据集3倍超分辨率为例,本文方法相较于次优方法HAUNet,PSNR和SSIM分别提升了0.11 dB和0.0033;在主观视觉质量方面,SAF2Net能够恢复出更多清晰的纹理细节。实验结果表明,本文所提出的SAF2Net能够从两个不同的角度挖掘混合尺度全局信息,并有效融合空间-频率互补特征,在遥感图像超分辨率任务中表现出具有竞争力的重建性能。展开更多
This paper is concerned with controller design of net- worked control systems （NCSs） with both network-induced delay and arbitrary packet dropout. By using a packet-loss-dependent Lyapunov function, sufficient condi...This paper is concerned with controller design of net- worked control systems （NCSs） with both network-induced delay and arbitrary packet dropout. By using a packet-loss-dependent Lyapunov function, sufficient conditions for state/output feedback stabilization and corresponding control laws are derived via a switched system approach. Different from the existing results, the proposed stabilizing controllers design is dependent on the packet loss occurring in the last two transmission intervals due to the network-induced delay. The cone complementary lineara- tion （CCL） methodology is used to solve the non-convex feasibility problem by formulating it into an optimization problem subject to linear matrix inequality （LMI） constraints. Numerical examples and simulations are worked out to demonstrate the effectiveness and validity of the proposed techniques.展开更多
为合理评价全可再生能源多能互补系统,提出了计及可再生能源资源禀赋的综合评价指标体系。首先,设计了仅用可再生能源进行供能的全可再生能源多能互补系统,包括系统结构、设备配置和运行策略;其次,根据指标构建原则建立了包含资源禀赋(...为合理评价全可再生能源多能互补系统,提出了计及可再生能源资源禀赋的综合评价指标体系。首先,设计了仅用可再生能源进行供能的全可再生能源多能互补系统,包括系统结构、设备配置和运行策略;其次,根据指标构建原则建立了包含资源禀赋(含资源储量和特性)等在内的综合评价指标体系;再次,针对引入的资源禀赋指标,采用层次分析法(analytic hierarchy process,AHP)-熵权-优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)组合法对系统进行综合评价。最后,根据地区气候差异选取5个代表性城市进行算例分析。分析结果表明,可再生能源资源禀赋与系统评价结果存在正相关性,资源禀赋指标的加入使得评价结果更加合理可靠,验证了所提评价体系的有效性;而所用评价方法不仅能有效地处理含资源禀赋在内的各项指标,还能使评价结果更具区分度,可为可再生能源多能互补系统优化配置等提供决策依据。展开更多
A parameter-self-adjusting Levenberg-Marquardt method （PSA-LMM） is proposed for solving a nonlinear system of equations F（x） = 0, where F ：R^n→R^n is a semismooth mapping. At each iteration, the LM parameter μk...A parameter-self-adjusting Levenberg-Marquardt method （PSA-LMM） is proposed for solving a nonlinear system of equations F（x） = 0, where F ：R^n→R^n is a semismooth mapping. At each iteration, the LM parameter μk is automatically adjusted based on the ratio between actual reduction and predicted reduction. The global convergence of PSA- LMM for solving semismooth equations is demonstrated. Under the BD-regular condition, we prove that PSA-LMM is locally superlinearly convergent for semismooth equations and locally quadratically convergent for strongly semismooth equations. Numerical results for solving nonlinear complementarity problems are presented.展开更多
文摘现有大多遥感图像超分辨率方法,无法充分挖掘图像中混合尺度的自相似性信息和跨尺度区域间的关联信息,且忽略了频率域对感知图像高频信息的能力。针对这一问题,本文提出了一种空间自适应及频率融合网络(Spatial Adaptation and Frequency Fusion Network,SAF2Net)。SAF2Net首先引入一种混合尺度空间自适应特征调制模块,采用类似于特征金字塔的方式获取不同尺度下的判别特征,丰富多尺度特征的表达能力。随后,设计了一个全局多尺度感受野选择块,挖掘跨尺度区域间的关联特征。在此基础上,引入空间自适应选择块和频率分离选择块,融合空间-频率互补信息以增强局部特征,提高模型对图像高频内容的建模能力。在两个公开遥感图像数据集上进行多组实验,SAF2Net获得的定量评价指标结果均优于其他对比方法。以UCMerced数据集3倍超分辨率为例,本文方法相较于次优方法HAUNet,PSNR和SSIM分别提升了0.11 dB和0.0033;在主观视觉质量方面,SAF2Net能够恢复出更多清晰的纹理细节。实验结果表明,本文所提出的SAF2Net能够从两个不同的角度挖掘混合尺度全局信息,并有效融合空间-频率互补特征,在遥感图像超分辨率任务中表现出具有竞争力的重建性能。
基金supported by the National Natural Science Foundation of China (6093400761174059)+1 种基金the Program for New Century Excellent Talents (NCET-08-0359)the Shanghai RisingStar Tracking Program (11QH1401300)
文摘This paper is concerned with controller design of net- worked control systems （NCSs） with both network-induced delay and arbitrary packet dropout. By using a packet-loss-dependent Lyapunov function, sufficient conditions for state/output feedback stabilization and corresponding control laws are derived via a switched system approach. Different from the existing results, the proposed stabilizing controllers design is dependent on the packet loss occurring in the last two transmission intervals due to the network-induced delay. The cone complementary lineara- tion （CCL） methodology is used to solve the non-convex feasibility problem by formulating it into an optimization problem subject to linear matrix inequality （LMI） constraints. Numerical examples and simulations are worked out to demonstrate the effectiveness and validity of the proposed techniques.
文摘为合理评价全可再生能源多能互补系统,提出了计及可再生能源资源禀赋的综合评价指标体系。首先,设计了仅用可再生能源进行供能的全可再生能源多能互补系统,包括系统结构、设备配置和运行策略;其次,根据指标构建原则建立了包含资源禀赋(含资源储量和特性)等在内的综合评价指标体系;再次,针对引入的资源禀赋指标,采用层次分析法(analytic hierarchy process,AHP)-熵权-优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)组合法对系统进行综合评价。最后,根据地区气候差异选取5个代表性城市进行算例分析。分析结果表明,可再生能源资源禀赋与系统评价结果存在正相关性,资源禀赋指标的加入使得评价结果更加合理可靠,验证了所提评价体系的有效性;而所用评价方法不仅能有效地处理含资源禀赋在内的各项指标,还能使评价结果更具区分度,可为可再生能源多能互补系统优化配置等提供决策依据。
基金Acknowledgments. This work is supported by the National Natural Science Foundation of China under projects Nos. 11071029, 11101064 and 91130007 and speciMized Research Fund for the Doctoral Program of Higher Education （20110041120039）. We are grateful to the associate editor and anonymous referee＇s comments to improve the quality of the manuscript. The second author also appreciate the discussion with his student Miao Xiaonan.
文摘A parameter-self-adjusting Levenberg-Marquardt method （PSA-LMM） is proposed for solving a nonlinear system of equations F（x） = 0, where F ：R^n→R^n is a semismooth mapping. At each iteration, the LM parameter μk is automatically adjusted based on the ratio between actual reduction and predicted reduction. The global convergence of PSA- LMM for solving semismooth equations is demonstrated. Under the BD-regular condition, we prove that PSA-LMM is locally superlinearly convergent for semismooth equations and locally quadratically convergent for strongly semismooth equations. Numerical results for solving nonlinear complementarity problems are presented.
