用演化算法求解抛物型方程扩散系数的识别问题

基于演化算法给出了一类求解参数识别反问题的一般方法,该方法表明只要找到好的、求解相应的正问题的数值方法,演化算法就可以用于求解此类反问题。设计有效的求解反问题的演化算法的关键是寻找一种适合反问题的解空间的编码表示形式、适当的适应值函数形式以及有效的计算正问题的数值方法。该文结合算法、传统的求解反问题的工方法和正则化技术,设计了一类求解参数识别反问题的方法。为验证此类方法,将其用于求解一维扩散方程的     

Separation of Transparent Layers using Focus

Consider situations where the depth at each point in the scene is multi-valued, due to the presence of a virtual image semi-reflected by a transparent surface. The semi-reflected image is linearly superimposed on the image of an object that is behind the transparent surface. A novel approach is proposed for the separation of the superimposed layers. Focusing on either of the layers yields initial separation, but crosstalk remains. The separation is enhanced by mutual blurring of the perturbing components in the images. However, this blurring requires the estimation of the defocus blur kernels. We thus propose a method for self calibration of the blur kernels, given the raw images. The kernels are sought to minimize the mutual information of the recovered layers. Autofocusing and depth estimation in the presence of semi-reflections are also considered. Experimental results are presented.     

Robot arm reaching through neural inversions and reinforcement learning

We present a neural method that computes the inverse kinematics of any kind of robot manipulators, both redundant and non-redundant. Inverse kinematics solutions are obtained through the inversion of a neural network that has been previously trained to approximate the manipulator forward kinematics. The inversion provides difference vectors in the joint space from difference vectors in the workspace. Our differential inverse kinematics (DIV) approach can be viewed as a neural network implementation of the Jacobian transpose method for arm kinematic control that does not require previous knowledge of the arm forward kinematics. Redundancy can be exploited to obtain a special inverse kinematic solution that meets a particular constraint (e.g. joint limit avoidance) by inverting an additional neural network The usefulness of our DIV approach is further illustrated with sensor-based multilink manipulators that learn collision-free reaching motions in unknown environments. For this task, the neural controller has two modules: a reinforcement-based action generator (AG) and a DIV module that computes goal vectors in the joint space. The actions given by the AG are interpreted with regard to those goal vectors.     

应力-强度模型可靠性评估的仿真分析

在应力－强度干涉模型中,当应力、强度均服从正态分布,且分布参数未知的情况下,讨论了给定验前分布情况下的可靠性Ｂａｙｅｓ精确下限,同时给出了无验前信息时的可靠性Ｂａｙｅｓ精确下限。鉴于精确限计算的性,给出了应力－强度模型可靠性下限的近似计算方法,同时给出了可靠性的近似分布,最后,利用Ｍｏｎｔｅ－Ｃａｒｌｏ方法分析了近似算法的精度。     

基于壳聚糖包埋二氧化硅-亚甲基蓝纳米复合物的电流型癌胚抗原免疫传感器的研究

合成了一种新型的SiO2-亚甲基蓝(SiO2-MB)纳米复合物.SiO2-MB纳米复合物具有不同于一般的纳米SiO2的性质,它能将MB的电子转移到电极表面,而且更重要的是减小了MB的渗漏.SiO-MB纳米复合物作为免疫传感器的媒介体使用,并采用壳聚糖(CS)包埋此复合物形成CS-SiO2-MB复合膜滴涂于洁净的玻碳电极(GCE)表面,然后在复合膜的表面固定纳米金(nano-Au)并吸附癌胚抗体(anti-CEA),制备出了性能良好的电流型免疫传感器.通过循环伏安考察了电极的电化学特性,并采用透射电子显微镜(TEM)对SiO2-MB纳米复合物的微观结构进行了表征.在最优条件下,该传感器在癌胚抗原(CEA)浓度为1～80 ng/mL范围内有良好的线性关系,检测下限为0.3 ng/mL(3倍信噪比).而且,该传感器制作简单,检测快速,稳定性较好.     

仿人机器人逆运动学在线求解方法研究

针对仿人机器人逆运动学在线求解问题,从计算实时性与数值稳定性的角度展开研究。分析了仿人机器人下肢拓扑结构,建立其运动学模型与前向运动学描述,根据当前机器人逆运动学算法研究成果,将几何方法与阻尼最小二乘法相结合,并结合分段阻尼思想,提出一种仿人机器人在线逆运动学求解算法。根据运动规划结果,将所提方法与基于雅可比矩阵的广义逆方法通过仿真算例进行对比,验证了所提方法在奇异位形附近的数值稳定性和在线实施的可行性。     

Structural, electronic, and magnetic properties of heterofullerene C(58)Si with odd number of atoms and a near planar tetracoordinate Si atom

Density functional calculations and minimization techniques have been employed to characterize the structural and electronic properties of [5,6]-heterofullerene-C₅₈Si-C_2v. Since it has odd number of atoms and a near planar tetracoordinate Si atom on the skeleton of the cage, it has odd number of atoms assembling a cage and is a novel molecule. Vibrational frequencies of the molecule have been calculated at the B3LYP/6-31G* level of theory. The absence of imaginary vibrational frequency confirms that the molecule corresponds to a true minimum on the potential energy hypersurface. Sixteen ¹³C nuclear magnetic resonance (NMR) spectral signals of C₅₈Si are characterized, and its heat of formation was estimated in this work.     

神经网络直接逆控制在无人机飞控系统中的应用研究

针对无人机发生故障时系统的非线性耦合特性,提出了一种基于神经网络直接逆控制的飞行控制方法,用于在飞机发生故障时进行控制律重构以恢复对飞机的控制;根据无人机发生故障时非线性运动的特点,确定适当的神经网络结构建立无人机非线性系统的逆系统,并与被控对象串连可以对非线性耦合系统进行线性化解耦,然后引入PID反馈控制进一步提高神经网络逆控制系统的性能;仿真分析表明该方法在无人机发生故障采用传统PID控制失效时,在误差允许范围内可以用来对无人机进行控制。     

从一道C＋＋程序看浮点数的存储格式

通过一个示例程序深入剖析了不同类型的数据在机器中的存储格式,并根据IEEE754—1985标准,给出了计算过程.     

基于线性预测和位操作的信息隐藏算法

鉴于信息的安全性问题,信息隐藏技术也已成为信息安全领域的研究热点.利用图像中当前像素点邻近的相关像素的像素值,对该点的值进行线性预测.再根据预测的准确度,确定相应的阈值,并结合位操作,提出了一种新的简单易于实现的信息隐藏算法.并在Lena图像上进行了实验,得到了隐藏率为0.160bits/Byte,信噪比为42.276dB的结果.经初步测试,证明了在保证较高隐藏率的前提下,能够较好地提高信噪比.