具有良好宽容性的逆波束形成干扰抑制算法研究

在阵列信号处理中,逆波束形成干扰抑制算法利用干扰的方位信息估计干扰信号从而进行干扰抑制,但在复杂海洋环境中阵列接收的干扰信号往往存在相位随机扰动,此方法估计的干扰信号与实际干扰信号有较大偏差,造成干扰抑制效果不理想。为适应干扰相位的随机扰动,具有良好宽容性的逆波束形成干扰抑制算法充分考虑随机扰动的存在,利用干扰重建矩阵估计干扰信号,此时估计干扰信号更接近实际干扰信号,保证干扰抑制有较好的结果。该文算法充分考虑了复杂海洋环境中干扰信号的相位扰动,可以获得较好的干扰抑制效果,提高了算法的宽容性。理论分析、计算机仿真结果均表明该文算法的有效性。     

A cone programming approach to the bilinear matrix inequality problem and its geometry

We discuss an approach for solving the Bilinear Matrix Inequality (BMI) based on its connections with certain problems defined over matrix cones. These problems are, among others, the cone generalization of the linear programming (LP) and the linear complementarity problem (LCP) (referred to as the Cone-LP and the Cone-LCP, respectively). Specifically, we show that solving a given BMI is equivalent to examining the solution set of a suitably constructed Cone-LP or Cone-LCP. This approach facilitates our understanding of the geometry of the BMI and opens up new avenues for the development of the computational procedures for its solution. Research supported in part by the National Science Foundation under Grant CCR-9222734.     

基于兴趣点方向梯度直方图的图像检索方法

提出了一种基于图像兴趣点方向梯度直方图的检索方法.为了提高检索准确度,首先采用直方图均衡化增强图像对比度,然后利用SURF(Speeded Up Robust Features)检测子检测图像中的兴趣点,以兴趣点为中心,对兴趣点邻域内分块方向梯度直方图进行图像特征描述,最后进行相似性度量.该算法通过直方图均衡化,提取到图像中更丰富的细节信息尤其对于颜色单一与颜色较深的图像,而且算法中充分利用了图像中包含信息量较多的图像兴趣点.实验证明,该算法提高了图像检索的准确度,相比其他算法取得了更好的检索结果.     

Direct synthesis of porous NiO nanowall arrays on conductive substrates for supercapacitor application

Porous NiO nanowall arrays (NWAs) grown on flexible Fe-Co-Ni alloy have been successfully synthesized by using nullaginite (Ni₂(OH)₂CO₃) as precursor and investigated as supercapacitor electrodes. In details, we adopted a simple hydrothermal method to realize Ni₂(OH)₂CO₃ NWAs and examined their robust mechanical adhesion to substrate via a long-time ultrasonication test. Porous NiO NWAs were then obtained by a post-calcination towards precursors at 500 °C in nitrogen atmosphere. Electrochemical properties of as-synthesized NiO NWAs were evaluated by cyclic voltammetry and galvanostatic charge/discharge; porous NiO NWAs electrode delivered a specific capacitance of 270 F/g (0.67 A/g); even at high current densities, the electrode could still deliver a high capacitance up to 236 F/g (13.35 A/g). Meanwhile, it exhibited excellent cycle lifetime with ∼93% specific capacitance kept after 4000 cycles. These results suggest that as-made porous NiO NWAs electrode is a promising candidate for future thin-film supercapacitors and other microelectronic systems.     

Robust and accurate inference for generalized linear models

In the framework of generalized linear models, the nonrobustness of classical estimators and tests for the parameters is a well known problem, and alternative methods have been proposed in the literature. These methods are robust and can cope with deviations from the assumed distribution. However, they are based on first order asymptotic theory, and their accuracy in moderate to small samples is still an open question. In this paper, we propose a test statistic which combines robustness and good accuracy for moderate to small sample sizes. We combine results from Cantoni and Ronchetti [E. Cantoni, E. Ronchetti, Robust inference for generalized linear models, Journal of the American Statistical Association 96 (2001) 1022–1030] and Robinson, Ronchetti and Young [J. Robinson, E. Ronchetti, G.A. Young, Saddlepoint approximations and tests based on multivariate M-estimators, The Annals of Statistics 31 (2003) 1154–1169] to obtain a robust test statistic for hypothesis testing and variable selection, which is asymptotically χ²-distributed as the three classical tests but with a relative error of order O(n⁻¹). This leads to reliable inference in the presence of small deviations from the assumed model distribution, and to accurate testing and variable selection, even in moderate to small samples.     

Relaxed robust second-order-cone programming

In this paper, we propose an approximate optimization model for the robust second-order-cone programming problem with a single-ellipsoid uncertainty set for which the computational complexity is not known yet. We prove that this approximate robust model can be equivalently reformulated as a finite convex optimization problem.     

Robust supergain beamforming for circular array via second-order cone programming

The phenomenon of supergain for a circular array and its robust beamforming are presented. The coplanar superdirective array gain of the circular array, although it is not so extreme as an endfire line array, outperforms a lot over that of a conventional delay-and-sum beamformer in isotropic noise fields when the inter-element spacings are much smaller than one-half wavelength. However, optimum beamforming algorithms can be extremely sensitive to slight errors in array characteristics. The performance are known to degrade significantly if some of underlying assumptions on the sensor array is violated. Therefore, white noise gain constraint is used to improve the robustness of the supergain beamformer against random errors. We show that the design of the weight vector of robust supergain beamformer can be reformulated as a form of second-order cone programming and resolved efficiently via the well-established interior point method. Results of computer simulation for a 24-element circular array confirm satisfactory performance of the approach proposed in this paper.     

Duality in robust optimization: Primal worst equals dual best

We study the dual problems associated with the robust counterparts of uncertain convex programs. We show that while the primal robust problem corresponds to a decision maker operating under the worst possible data, the dual problem corresponds to a decision maker operating under the best possible data.     

四分位数z比分数法在能力验证过程的改进-高斯节点分位数z比分数法

通过对四分位数稳健统计进行Z比分数法能力验证过程的分析提出高斯节点z比分数法。