This paper presents an optimized 64-bit parallel adder, Sparse-tree architecture enames low carry-merge fan-outs and inter-stage wiring complexity. Single-rail and semi-dynamic circuit improves operation speed. Simula...This paper presents an optimized 64-bit parallel adder, Sparse-tree architecture enames low carry-merge fan-outs and inter-stage wiring complexity. Single-rail and semi-dynamic circuit improves operation speed. Simulation results show that the proposed adder can operate at 485ps with power of 25.6mW in 0.18μm CMOS process. It achieves the goal of higher speed and lower power.展开更多
Sparse-tree land is one of the typical lands and can be considered as one typical rough surface in boundary layer meteorology. Many lands can be classified into the kind surface in the view of scaIe and distribution f...Sparse-tree land is one of the typical lands and can be considered as one typical rough surface in boundary layer meteorology. Many lands can be classified into the kind surface in the view of scaIe and distribution feature of the roughness elements such as agroforest, scatter planted or growing trees, savanna and so on. The structure of surface boundary layer in sparse-tree land is analyzed and the perameters, friction velocity u*and roughness length zo are deduced based on energy balance law and other physical hypothesis. The models agree well with data of wind tunnel experiments and field measurements.展开更多
基于SURF(Speeded Up Robust Features)特征点提取是目前比较流行的图像配准方法.本文在SURF基础上,提出一种基于分块策略的改进方法:首先采用分水岭分割法确定图像的分块数量,然后对图像进行分块,每个子块提取一定数量的特征点,以便实...基于SURF(Speeded Up Robust Features)特征点提取是目前比较流行的图像配准方法.本文在SURF基础上,提出一种基于分块策略的改进方法:首先采用分水岭分割法确定图像的分块数量,然后对图像进行分块,每个子块提取一定数量的特征点,以便实现特征点的均匀提取;再通过稀疏特征树法找出匹配的特征点对;最后用RANSAC算法剔除错误匹配特征点对,同时计算参考图像与待配准图像的变换关系.实验表明,该方法能够高效、快速地解决遥感图像的自动配准问题.展开更多
A design method based on the tree-model structure for topology update is presented. The routing tree of every node in network is built by defining the data structure and is used to save the topology information of nei...A design method based on the tree-model structure for topology update is presented. The routing tree of every node in network is built by defining the data structure and is used to save the topology information of neighbor nodes. The node topology update is accomplished by exchanging their routing trees. For saving the precious wireless bandwidth, the routing tree is sparsely shaped before sending by pruning the redundant routing information. Then, the node topology update is implemented by using algorithms of inserting and deleting routing sub-trees.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos. 60273069, 60376018, 90207011, the National High Technology Development 863 Program of China under Grant No. 2002AAl10020, and the Adwnced Research Foundation of NUDT under Grant No. JC03-06-007.
文摘This paper presents an optimized 64-bit parallel adder, Sparse-tree architecture enames low carry-merge fan-outs and inter-stage wiring complexity. Single-rail and semi-dynamic circuit improves operation speed. Simulation results show that the proposed adder can operate at 485ps with power of 25.6mW in 0.18μm CMOS process. It achieves the goal of higher speed and lower power.
文摘Sparse-tree land is one of the typical lands and can be considered as one typical rough surface in boundary layer meteorology. Many lands can be classified into the kind surface in the view of scaIe and distribution feature of the roughness elements such as agroforest, scatter planted or growing trees, savanna and so on. The structure of surface boundary layer in sparse-tree land is analyzed and the perameters, friction velocity u*and roughness length zo are deduced based on energy balance law and other physical hypothesis. The models agree well with data of wind tunnel experiments and field measurements.
文摘基于SURF(Speeded Up Robust Features)特征点提取是目前比较流行的图像配准方法.本文在SURF基础上,提出一种基于分块策略的改进方法:首先采用分水岭分割法确定图像的分块数量,然后对图像进行分块,每个子块提取一定数量的特征点,以便实现特征点的均匀提取;再通过稀疏特征树法找出匹配的特征点对;最后用RANSAC算法剔除错误匹配特征点对,同时计算参考图像与待配准图像的变换关系.实验表明,该方法能够高效、快速地解决遥感图像的自动配准问题.
文摘A design method based on the tree-model structure for topology update is presented. The routing tree of every node in network is built by defining the data structure and is used to save the topology information of neighbor nodes. The node topology update is accomplished by exchanging their routing trees. For saving the precious wireless bandwidth, the routing tree is sparsely shaped before sending by pruning the redundant routing information. Then, the node topology update is implemented by using algorithms of inserting and deleting routing sub-trees.
文摘为了提高利用合成孔径雷达(synthetic aperture radar,SAR)图像对目标型号识别的能力,在稀疏表示识别方法的基础上,提出了一种树形框架稀疏编码的雷达目标识别方法。稀疏编码树是由多个节点构成的分类器,其上每个节点由不同识别需求的子分类器构成。在训练阶段,分别针对目标型号识别需求以及型号识别需求学习相应分类器,组成分类器的根节点和子节点。识别阶段在根节点位置完成对目标类别的判断,再根据根节点的判断结果,对存在型号变体的目标,在子节点上再对型号进行识别,最终输出目标的识别结果,而不存在型号变体的目标则直接输出识别结果。基于美国运动和静止目标获取与识别(moving and stationary target acquisition and recognition,MSTAR)计划录取的SAR图像数据集上的实验结果表明,树形结构在取得与主流方法相当的目标类别识别精度的前提下,提高了对目标型号的识别能力,同时能够准确输出目标类别识别结果。
