基于相对调制度的非方形干涉图处理方法

以相对调制度作为判据,划分干涉图中的有效点和无效点,并据此进行加权,采用加权最小二乘算法进行去包裹处理.采用这种方法可以有效减小包裹位相中坏点或无信息点对有效点去包裹位相的影响.以移相式干涉仪为例,给出了相对调制度的计算方法,简述了加权最小二乘去包裹算法的原理,并通过光学盘片的处理结果验证方法的正确性.     

PARAMETERIZATION OF TRIANGULAR MESHES

A new algorithm called the weighted least square discrete parameterization (WLSDP) is presented for the parameterization of triangular meshes over a convex planar region. This atgorithm is the linear combination of the discrete Conformal mapping (DCM) and the discrete Authalic mapping (DAM). It provides the good properties of both DCM and DAM, such as robustness and low distortion. By adjusting the scaling factor q embedded in the WLSDP, satisfactory parameterizations in different special applications can be achieved.     

条件中位数量近邻估计误差分布的Edgeworth展式及其随机加权法

在本中，我们得到了条件中位数最近邻估计误差分布的渐近展示。为了模拟条件中位数最近邻估计之误差分布，我们使用了随机加权法，并证明了利用随机加权法来逼近条件中位数最近邻估计误差分布的精度为o(n^d 2^-(logn)^ε），（ε：＞0）。     

非线性问题的MPS无网格算法

给出了修正的MPS(Moving Particle Semi-implicit)无网格方法,指出恰当选取权函数可避免使用虚节点来处理边界,从而解决复杂边界处虚节点难设定的问题.以非线性Burgers方程为算例分析了其数值特性,结果表明:以样条函数为权函数时不采用虚节点的结果与使用虚节点的结果一致;对一维问题,光滑权函数性能明显优于非光滑权函数;而对二维问题,近边界处加权域不对称性的影响则不很显著.与精确解或由传统方法所得结果的对比分析表明该方案可行.该方法物理概念清晰,易于编程实现.      

双时间步长加权ENO-强紧致高分辨率格式及在叶轮机械非定常流动中的应用

在非结构网格下,针对非定常三维N-S方程组发展了一种双时间步长高精度快速迭代格式。该格式在时间上具有二阶精度,在空间上将r=3的加权ENO格式与强紧致格式相结合去处理N-S方程中的对流项以及离散方程的右端项,并用四阶精度的紧致格式去计算N-S方程中的粘性项。典型的3个算例从不同侧面对格式进行了考核。计算表明:该算法具有高效率与高分辨率的特征,所得的计算结果与相关实验数据比较吻合,初步表明了该算法可以在非结构网格下模拟非定常流动的物理过程。      

时变加权LQT设计方法理论推导及应用

利用矩阵运算公式和极值原理,对时变加权性能指标下的线性二次型跟踪器(LQT)迭代方程进行了理论推导。以F-16飞机为例,利用飞行控制经验构建俯仰速率控制系统线性框图。在MATLAB/Simulink环境下,针对两种时变加权性能指标和一种定常加权性能指标,利用多变量优化算法完成了一个状态点的控制律参数设计,并进行了时域和频域对比分析,初步验证了时变加权LQT设计方法的工程可行性和有效性。     

Weighted marginal fisher analysis with spatially smooth for aircraft recognition

Due to limitations to extract invariant features for recognition when the aircraft presents various poses and lacks enough samples for training, a novel algorithm called Weighted Marginal Fisher Analysis with Spatially Smooth （WMFA-SS） for extracting invariant features in aircraft rec- ognition is proposed. According to the Graph Embedding （GE） framework, Heat Kernel function is firstly introduced to characterize the interclass separability when choosing the weights of penalty graph. Furthermore, Laplacian penalty is applied to constraining the coefficients to be spatially smooth in this algorithm. Laplacian penalty is able to incorporate the prior information that neigh- boring pixels are correlated. Besides, using a Laplacian penalty can also avoid the singularity of Laplacian matrix of intrinsic graph. Once compact representations of the images are obtained, it can be considered as invariant features and then be performed in classification to recognize different patterns of aircraft. Real aircraft recognition experiments show the superiority of our proposed WMFA-SS in comparison to other GE algorithms and the current aircraft recognition algorithm; the accuracy rate of our proposed method is 90.00% for dataset BH-AIR1.0 and 99.25% for dataset BH-AIR2.0.     

分形级摄法在振动问题中的应用

用戴劳级数的推广－分形级数代替原有摄动方法中的戴劳级数，并讨论分级级数摄动法解振动问题的一般原则，在本文实例中，小参数项ε和ε^2分别变为ε^1.048389和ε^2.220377。在求解分形级数的指数时可应用加权残值法，如最小二乘法。