应用于地形匹配导航的激光高度计设计

为解决基于雷达高度表探测的地形匹配导航系统探测精度不高、易受电子干扰影响而失效、且在跨海飞行时无法导航的难题,设计了一种激光高度计来代替雷达高度表进行地形探测。采用二极管泵浦固体激光器技术设计激光发射装置,输出近红外/蓝绿双波长激光,既可以测量陆地地形高度,又可以穿透海水探测海底地形;并根据激光高度计拟达到的性能指标选择合适的光电探测器,优化设计了光学系统、扫描系统和信号处理系统。所设计的激光高度计具有体积小、重量轻、高重频、探测灵敏度高、抗电磁干扰能力强等特点。     

基于SIFT匹配的全局运动估计方法

提出了一种基于SIFT(Scale invariant feature transform)匹配的全局运动估计算法.在SIFT初匹配的基础上,对每一个原始匹配特征点,利用所在尺度的邻域灰度信息,对其加权平均后再进行匹配,进而去除误配点.精炼后的匹配点集合作为求解全局运动参数模型的对应数据,采用最小二乘法计算模型参数.在...     

基于局部轮廓特征的无人机头部检测跟踪算法

针对无人机的结构特点,提出了一种基于目标轮廓提取、轮廓自动分段、头部定位以及头部模板匹配四个模块的目标头部检测跟踪算法.首先对第一帧图像提取目标轮廓,并通过计算轮廓点的变化率,对轮廓进行自动分段,得到目标的4个局部轮廓点列,进而根据头部轮廓点列的特点,完成头部轮廓筛选,然后利用基于目标中轴的二次曲线拟合,实现头部顶点的...     

Recoupling in solid state NMR using γ prepared states and phase matching

The paper describes two-dimensional solid state NMR experiments that use powdered dephased antiphase coherence (γ preparation) to encode chemical shifts in the indirect dimension. Both components of this chemical shift encoded gamma-prepared states can be refocused into inphase coherence by a recoupling element. This helps to achieve sensitivity enhancement in 2D NMR experiments by quadrature detection. The powder dependence of the gamma-prepared states allows for manipulating them by suitable insertion of delays in the recoupling periods. This helps to design experiments that suppress diagonal peaks in 2D spectra, leading to improved resolution. We describe some new phase modulated heteronuclear and homonuclear recoupling pulse sequences that simplify the implementation of the described experiments based on γ prepared states. Recoupling in the heteronuclear spin system is achieved by matching the difference in the amplitude of the sine/cosine modulated phase on the two rf-channels to the spinning frequency while maintaining the same power on the two rf-channels.     

Efficient exponential-time algorithms for edit distance between unordered trees

The edit distance problem for rooted unordered trees is known to be NP-hard. Based on this fact, this paper studies exponential-time algorithms for the problem. For a general case, an $O(\min ({1.26}^{n_1+n_2},2^{b_1+b_2}\cdot \text{<mi mathvariant="italic" is="true">poly</mi>}(n_1,n_2)))$ time algorithm is presented, where $n_1$ and $n_2$ are the numbers of nodes and $b_1$ and $b_2$ are the numbers of branching nodes in two input trees. This algorithm is obtained by a combination of dynamic programming, exhaustive search, and maximum weighted bipartite matching. For bounded degree trees over a fixed alphabet, it is shown that the problem can be solved in $O({(1+ϵ)}^{n_1+n_2})$ time for any fixed $ϵ>0$. This result is achieved by avoiding duplicate calculations for identical subsets of small subtrees.     

Large deviation properties for patterns

Deciding whether a given pattern is over- or under-represented according to a given background model is a key question in computational biology. Such a decision is usually made by computing some p-values reflecting the “exceptionality” of a pattern in a given sequence or set of sequences. In the simplest cases (short and simple patterns, simple background model, small number of sequences), an exact p-value can be computed with a tractable complexity. The realistic cases are in general too complicated to get such an exact p-value. Approximations are thus proposed (Gaussian, Poisson, Large deviation approximations). These approximations are applicable under some conditions: Gaussian approximations are valid in the central domain while Poisson and Large deviation approximations are valid for rare events. In the present paper, we prove a large deviation approximation to the double strands counting problem that refers to a counting of a given pattern in a set of sequences that arise from both strands of the genome. In that case, dependencies between a sequence and its reverse complement cannot be neglected. They are captured here for a Bernoulli model from general combinatorial properties of the pattern. A large deviation result is also provided for a set of small sequences.     

Analysis of orthogonal multi-matching pursuit under restricted isometry property

Orthogonal multi-matching pursuit(OMMP)is a natural extension of orthogonal matching pursuit(OMP)in the sense that N(N≥1)indices are selected per iteration instead of 1.In this paper,the theoretical performance of OMMP under the restricted isometry property(RIP)is presented.We demonstrate that OMMP can exactly recover any K-sparse signal from fewer observations y=φx,provided that the sampling matrixφsatisfiesδKN-N+1+(K/N)~(1/2)θKN-N+1,N1.Moreover,the performance of OMMP for support recovery from noisy observations is also discussed.It is shown that,for l_2 bounded and l_∞bounded noisy cases,OMMP can recover the true support of any K-sparse signal under conditions on the restricted isometry property of the sampling matrixφand the minimum magnitude of the nonzero components of the signal.     

给定悬挂点数的双圈图中具有最小Hosoya指数的图

Let G be a graph. The Hosoya index Z（G） of a graph G is defined to be the total number of its matchings. In this paper, we characterize the graph with the smallest Hosoya index of bicyclic graphs with given pendent vertices. Finally, we present a new proof about the smallest Hosoya index of bicyclic graphs.