Off‐grid DoA estimation method of wideband signals

In this paper, an off‐grid direction of arrival (DoA) estimation method is proposed for wideband signals. This method is based on the sparse representation (SR) of the array covariance matrix. Similar to the time domain DoA estimation methods, the correlation function of the sources was assumed to be the same and known. A new measurement vector is obtained using the lower‐left triangular elements of the covariance matrix. The DoAs are estimated by quantizing the entire range of continuous angle space into discrete grid points. However, the exact DoAs may be located between two grid points; therefore, this estimation has errors. The accuracy of DoA estimation is improved by the minimization of the difference between the new measurement vector and its estimated values. Simulation results revealed that the proposed method can enhance the DoA estimation accuracy of wideband signals.     

LPNN-based approach for LASSO problem via a sequence of regularized minimizations

In compressive sampling theory, the least absolute shrinkage and selection operator (LASSO) is a representative problem. Nevertheless, the non-differentiable constraint impedes the use of Lagrange programming neural networks (LPNNs). We present in this article the -LPNN model, a novel algorithm that tackles the LASSO minimization together with the underlying theory support. First, we design a sequence of smooth constrained optimization problems, by introducing a convenient differentiable approximation to the non-differentiable -norm constraint. Next, we prove that the optimal solutions of the regularized intermediate problems converge to the optimal sparse signal for the LASSO. Then, for every regularized problem from the sequence, the -LPNN dynamic model is derived, and the asymptotic stability of its equilibrium state is established as well. Finally, numerical simulations are carried out to compare the performance of the proposed -LPNN algorithm with both the LASSO-LPNN model and a standard digital method.     

浅谈东深供水改造工程的设计监理工作

施工图阶段设计监理工作的内容归纳起来主要是对设计质量进行控制.依据<水利建设工程招标、施工图阶段设计监理试行规定>,其具体工作内容仅限于设计成果的合法性和安全性,没有充分发挥设计监理作用,对施工图阶段设计质量的理解是不全面的.施工图阶段的设计质量不仅仅是提交合法和安全的图纸,而且图纸的提交时限性、可实施性及经济性也应是考核设计质量的重要组成部分,为此东深供水改造工程的设计监理工作内容确定为"五项控制"和"两项权利",全面地对施工图阶段的设计质量进行控制.     

模拟信号的恢复及其误差研究

数模混合仿真中模拟信号的恢复及其误差对整个仿真过程具有重要影响。本文探讨了用零阶保持和一阶保持进行信号恢复的方法，比较了它们的误差及工作特点。特别指出了一阶保持中，由于存在积分器复原时间及数字机操作时间的影响而会带来附加的误差，因此一阶保持方法较难达到其理论的精度。     

电站锅炉制粉系统的爆炸原因与防范对策

火力发电厂制粉系统爆炸事故时有发生 ,重大设备损坏 ,造成了严重的经济损失。本文通过分析研究 ,找出制粉系统爆炸的原因 ,从措施上、煤的质量控制上及制粉系统结构改造上提出了防范的对策。     

Motion and structure interpretation of an optical switch

This paper focuses on tracking, reconstruction and motion estimation of a well-defined MEMS optical switch from a microscopic view. For out-of-view reconstruction, a homography capable of transforming feature points and feature lines between a microscopic image and a CAD model of the switch is implemented. The homography between two sequential microscopic images is decomposed and factorized for motion estimation. Optical flow has also been explored to provide rough estimations of rotation centre and angle. The paper also illustrates motion parameter optimization principles to deal with uncertainty inherent in micro world. After non-linear optimization, estimation accuracy for rotation angle and rotation centre can reach 0.06° and pixel level, respectively.     

浅析露天栈桥改造

结合工程实例，论述了露天栈桥产生裂缝和腐蚀的原因，对栈桥结构进行了评价，提出了加固方案及加固施工中应注意的事项，经使用证明，加固效果良好。     

带限信号高频重建的一种新的正则外推算法

本文提出生种新的带限信号的外推方法，该方法能够很好地抑制噪声干扰，且计算复杂性较低，本文给出算法，证明了收敛性，最后给出了误差计算机实验结果。     

最大熵重建的迭代凸I投影算法

本文探讨了用迭代凸Ｉ投影（ＩｔｅｒａｔｉｖｅＣｏｎｖｅｘＩ－Ｐｒｏｊｅｃｔｉｏｎ，ＩＣＩＰ）算法求解最大熵Ｘ－ＣＴ重建问题．其思路是将这个复杂问题转化为多个简单子问题，然后迭代地求解这种单约束子问题．理论证明，这种算法收敛并能收敛到问题的最大熵解．这种算法形式优美，仿真结果表明算法同时也是有效的．     

A generalized approach to the reconstruction of a restricted class of digitized planar curves

Reconstruction of an original continuous curve and the estimation of its parameters from the digitized version of the curve is a challenging problem, as quantization always causes some loss of information. In this paper, we have developed a scheme for reconstruction which is applicable to a class of curves having at the most two parameters. The class of curves for which the scheme works has also been characterized. We have shown that for one-parameter curves the exact domain of values of the parameter can be obtained. But in the two-parameter case, only the smallest rectangle containing the domain can be realised. The distinctive feature of our scheme is that it provides a unified approach to solve the reconstruction and the domain-finding problem for a class of curves.