Accurate mirror-based camera pose estimation with explicit geometric meanings

An accurate closed form solution is proposed to estimate camera pose by several mirrored reference object images acquired via a planar mirror under different unknown poses. Compared with state-of-the-art methods, our method is more accurate when there are more than three images and has explicit geometric meanings. This method also properly handles cases in which some of the mirror poses are parallel. The central idea is to minimize an error metric based on all reflections of rotation, which enables the camera rotation to be estimated directly by SVD of sum of mirrored camera rotations. After that, the camera translation is computed by solving a large system of linear equations to minimize object space collinearity error. Both synthesized data and real data experiments show the advantages of our approach.     

An improved SVD-based watermarking technique for copyright protection

The drawbacks of SVD-based image watermarking are false positive, robust and transparency. The former can be overcome by embedding the principal components of the watermark into the host image, the latter is dependent on how much the quantity (i.e., scaling factor) of the principal components is embedded. For the existing methods, the scaling factor is a fixed value; actually, it is image-dependent. Different watermarks need the different scaling factors, although they are embedded in the same host image. In this paper, two methods are proposed to improve the reliability and robustness. To improve the reliability, for the first method, the principal components of the watermark are embedded into the host image in discrete cosine transform (DCT); and for the second method, those are embedded into the host image in discrete wavelets transform (DWT). To improve the robustness, the particle swarm optimization (PSO) is used for finding the suitable scaling factors. The experimental results demonstrate that the performance of the proposed methods outperforms than those of the existing methods.     

Sliding mode control for two-time scale systems: stability issues

The paper presents some results on global exponential stability of linear time invariant systems with different time scales. The full system is decomposed in two reduced ones by means of singular perturbations and a smooth approximation of a Variable Structure Control is synthesized for each of them using Reaching Law approach. The global closed loop stability is then proved for the whole system using Lyapunov methods and a particular state space decomposition. Moreover a literal form for ε∗ (a parameter which measures the minimum separation between time scales) is derived.     

Stress intensity factors for an interfacial crack between an orthotropic half-plane bonded to a dissimilar orthotropic layer with a punch

The plane strain problem of determining Stress Intensity Factors (SIF) for a moving interfacial Griffith crack between an elastic orthotropic half-plane and a dissimilar orthotropic layer with a moving punch situated along the boundary of the layer have been considered. The problem is reduced to the solution of three simultaneous singular integral equations with Cauchy-type singularities. Expressions for SIF for the case of a general loading are obtained. Numerical results for some particular cases are also presented graphically.     

基于最优解耦的鲁棒故障检测方法研究

系统地研究了线性系统在模型参数变动和存在外部扰动下的控制系统故障的鲁棒故障检测方法。分析了在与干扰信号不能完全解耦的情况下,如何设计残差信号使其对模型参数变化及噪声不敏感,而对故障敏感,由此得出了对未知输入具有鲁棒性的条件方程式,并基于最优解耦理论,通过矩阵的奇异值分解实现了最优解耦。在给出的仿真实例中,验证了该文提出方法的有效性。     

基于稀疏重建的信号DOA估计

从稀疏信号重建角度提出了一种改进的波达方向(DOA)估计方法。由于最小冗余线阵(MRLA)能以较少的阵元数获得较大的阵列孔径,将MRLA与l1-SVD方法相结合估计信号的DOA。仿真结果表明,经多次实验验证,所提方法是有效的,相比l1-SVD方法可以估计出更多信源的DOA,并且可以用较少的阵元数估计更多的信源DOA,具有信源过载能力。     

222Rn在大气输运研究中的示踪应用

本文简要回顾了222Rn及其子体示踪应用的主要方面,介绍了国内外对利用222Rn及其子体在预报地震和大气物质输运研究这两方面的工作.对这些示踪应用而言,要进行准确的定量分析和数值模拟,必须对222Rn及其子体在大气中的输运规律有细致的了解,这一点可以通过研究其动力学特征,建立输运模型来实现.本文中列举了部分对222Rn及其子体输运模式的研究,对比上层大气中的简单输运模型,一个比较全面的222Rn输运模型还需要考虑地表层结大气中的复杂的动力学因素,并将其作为222Rn在上层大气输运模型中的下垫面边界条件.     

基于模极大值小波域和TLS-ESPRIT的振荡瞬态识别方法

对于电能质量扰动检测和定位中振荡瞬态的检测、识别,目前普遍采用的是时频特征矢量提取和智能模式识别方法,此类方法无法准确提取电能质量振荡瞬态信号不同频率分量的组成。结合模极大值小波域和总体最小二乘法旋转不变技术的信号参数估计(total least squares-estimation of signal parameters via rotational invariance techniques,TLS-ESPRIT)可以很好地实现振荡信号的检测与识别。对于输入信号,首先采用模极大值小波域检测振荡发生的起始时刻和终止时刻,然后利用振荡时间间隔内的信号建立观测空间矩阵,通过奇异值分解和总体最小二乘法实现特征值截尾,将采样信号观测空间分解为信号子空间和噪声子空间,得到振荡信号每个构成频率分量的相应参数。仿真结果证实了所提出方法的可行性。     

Ectropy of diversity measures for populations in Euclidean space

Measures to evaluate the diversity of a set of points (population) in Euclidean space play an important role in a variety of areas of science and engineering. Well-known measures are often used without a clear insight into their quality and many of them do not appropriately penalize populations with a few distant groups of collocated or closely located points. To the best of our knowledge, there is a lack of rigorous criteria to compare diversity measures and help select an appropriate one. In this work we define a mathematical notion of ectropy for classifying diversity measures in terms of the extent to which they tend to penalize point collocation, we investigate the advantages and disadvantages of several known measures and we propose some novel ones that exhibit a good ectropic behavior. In particular, we introduce a quasi-entropy measure based on a geometric covering problem, three measures based on discrepancy from uniform distribution and one based on Euclidean minimum spanning trees. All considered measures are tested and compared on a large set of random and structured populations. Special attention is also devoted to the complexity of computing the measures. Most of the novel measures compare favorably with the classical ones in terms of ectropy. The measure based on Euclidean minimum spanning trees turns out to be the most promising one in terms of the tradeoff between the ectropic behavior and the computational complexity.     

谱估计方法的通用矩阵表示与新的谱估计方法

本文指出几种常见的谱估计方法可以归结为同一数学问题并可用同一矩阵方程表示。从这通用矩阵表示可导出许多新的谱估计方法。本文还具体研究了相关阵特征矢量空间谱估计方法,得出一些有益的结论。