微带印刷天线辐射与散射的全波分析方法

本文给出了一种分析微带印刷天线辐射与散射的数值方法。此方法将印刷天线按三角网格剖分，在导体表面建立积分方程，用全波离散镜像理论给出微带结构的空域格林函数的闭合表达式，未知电流用三角网格上的矢量电流基函数展开并用矩量法求解。与以往的矩形网格上基函数展开相比，此方法能更有效地逼近任意形状的微带结构，最后给出了几个数值结果     

A Fast Algorithm to Map Functions Forward

Mapping functions forward is required in image warping and other signal processing applications. The problem is described as follows: specify an integer d 1, a compact domain D R ^d, lattices L ₁,L ₂ R ^d, and a deformation function F : D R ^d that is continuously differentiable and maps D one-to-one onto F(D). Corresponding to a function J : F(D) R, define the function I = J F. The forward mapping problem consists of estimating values of J on L ₂ F(D), from the values of I and F on L ₁ D. Forward mapping is difficult, because it involves approximation from scattered data (values of I F ^-1 on the set F(L ₁ $#x22C2; D)), whereas backward mapping (computing I from J) is much easier because it involves approximation from regular data (values ofJ on L ₂ D). We develop a fast algorithm that approximates J by an orthonormal expansion, using scaling functions related to Daubechies wavelet bases. Two techniques for approximating the expansion coefficients are described and numerical results for a one dimensional problem are used to illustrate the second technique. In contrast to conventional scattered data interpolation algorithms, the complexity of our algorithm is linear in the number of samples.     

基于伪zernike矩的车牌字符识别

基于伪zernike矩的不变性,提出了基于伪zernike矩特征提取的车牌字符识别方法。在车牌区域定位的基础上,通过对图像的二值化过程和字符图像分割等一系列处理,在进行归一化处理后分别提取伪zernike的高阶矩。将提取的伪zernike矩作为字符的特征描述输入到BP神经网络进行训练,最后进行车牌字符分类识别。通过实验证明了该方法的的可行性。测试结果表明,这种方法实用有效,识别效果优于HU矩和zernike矩。而且可以计算出错误率和可识别的最佳矩,减小了计算量且增强了字符识别的实时性。     

Geometrically resilient color image zero-watermarking algorithm based on quaternion Exponent moments

Although research on zero-watermarking has made great progress in recent years, most of it has been focused on grayscale images rather than color ones, and cannot resist geometric attacks efficiently. In this paper, we discuss properties of quaternion Exponent moments (QEMs) in detail and propose a robust color image zero-watermarking algorithm which is robust to geometric attacks. We first compute and select robust QEMs of the original color image, and then a binary feature image is constructed using the magnitude of the selected moments. Eventually, a bitwise exclusive-or is applied on the binary feature image and a scrambled binary logo to generate the zero-watermark image. Experimental results show that the proposed zero-watermarking algorithm is robust to both geometric attacks and common image processing attacks effectively. Compared to similar zero-watermarking algorithms and traditional watermarking algorithms based on QEMs, the proposed zero-watermarking algorithm has better performance.     

Design and analysis of implantable CPW fed bowtie antenna for ISM band applications

A novel implantable coplanar waveguide (CPW) fed crossed bowtie antenna is proposed for short-range biomedical applications. The antenna is designed to resonate at 2.45 GHz, one of the industrial-scientific-medical (ISM) bands. It is investigated by use of the method of moments design equations and its simulation software (IE3D version 15). The size of the antenna is 371.8 mm³ (26 mm × 22 mm × 0.65 mm). The simulated and analyzed return losses are −23 and −25 dB at the resonant frequency of 2.45 GHz. We have analyzed some more performances of the proposed antenna and the results show that the proposed antenna is a perfect candidate for implantation. The proposed antenna has substantial merits like low profile, miniaturization, lower return loss and better impedance matching with high gain over other implanted antennas.     

Gaussian-Hermite moment-based depth estimation from single still image for stereo vision

Depth information of objects plays a significant role in image-based rendering. Traditional depth estimation techniques use different visual cues including the disparity, motion, geometry, and defocus of objects. This paper presents a novel approach of focus cue-based depth estimation for still images using the Gaussian-Hermite moments (GHMs) of local neighboring pixels. The GHMs are chosen due to their superior reconstruction ability and invariance properties to intensity and geometric distortions of objects as compared to other moments. Since depths of local neighboring pixels are significantly correlated, the Laplacian matting is employed to obtain final depth map from the moment-based focus map. Experiments are conducted on images of indoor and outdoor scenes having objects with varying natures of resolution, edge, occlusion, and blur contents. Experimental results reveal that the depth estimated from GHMs can provide anaglyph images with stereo quality better than that provided by existing methods using traditional visual cues.     

Elastoplastic Finite Element Analysis and Strength Evaluation of Adhesive Butt Joints of Similar and Dissimilar Hollow Shafts Subjected to External Bending Moments

Stress distributions and deformation of adhesive butt joints are analyzed by an elastoplastic finite element method when the joints of similar and dissimilar shafts are subjected to external bending moments. The effects of the ratio of Young's modulus for the adherends to that for an adhesive and the effects of the adhesive thickness on the interface stress distribution are investigated. Joint strength is predicted by using the elastoplastic interface stress distributions. It is found that the singular stress at the edge of the interfaces increases with an increase of the ratio of Young's modulus. Measurement of strains in joints and experiments on joint strength were conducted. The numerical results are in fairly good agreement with the experimental results. It is observed that the joint strength for dissimilar shafts are smaller than those for similar shafts. A fracture of dissimilar adhesive up-bonded shafts occurred from the interface of the adherend with smaller Young's modulus. It is seen that joint strength increases as the adhesive thickness increases.     

基于最小二乘法的正交多项式级数在谐波估计中的应用

利用基于最小二乘法的正交多项式级数来逼近谐波的概率密度函数并估计其95%不超过概率值。根据电力谐波测量样本统计样本的阶矩(原点矩);对于多变量或多矢量求和,首先建立求和模型,在统计出分量阶矩的基础上通过递归方法计算和的阶矩。基于最小二乘法的思想,确定逼近的正交多项式级数展开中的待定系数。这种方法不要求谐波的幅值和相位具有某种特定分布,适用范围广。最后用实例证明了该方法的有效性。