基于协同优化算法的Reed-Solomon码迭代软判决译码

基于协同优化算法推导出一种Reed-Solomon(RS)码的迭代软判决译码(SDD)算法。该算法属于消息传递算法,具有严格的理论基础。仿真结果表明,该算法相对于硬判决译码(HDD)能够获得有效的软判决译码增益,对于(15,9)RS码在误帧率(FER)为4×10-4时有0.3~1.3dB的增益;同时译码复杂度低,具有很好的工程实用性。此外该算法是一类软输入软输出(SISO)译码算法,能够应用于以RS码为子码的复合码,如级连码和乘积码的迭代译码。     

二维直方图区域斜分Otsu阈值分割的快速迭代算法

鉴于现有的基于二维直方图区域直分的阈值选取方法中存在明显的错分,提出了一种新的二维直方图区域斜分方法,导出了基于二维直方图区域斜分的otsu法的快速迭代算法.在实验结果中给出了分割结果和运行时间,并与基于二维直方图直分的Otsu原始算法及其他两种快速算法进行了比较.结果表明所提出的快速迭代算法,使分割后的图像内部区域均匀,边界形状准确,有稳健的抗噪性,同时运行时间大幅减少.     

Hilbert空间中一般强混合变分包含的迭代算法

研究了Hilbert空间中求一般强混合变分包含逼近解的迭代算法。这类变分包含概括了若干熟知的变分不等式与变分包含成特例。结果是刘理蔚与李育强(2001)及Noor(1998)的结果的推广和改进。     

C型压力机机身的轻量化设计

通过对C型压力机的机身结构进行强度和刚度分析,构建了机身参数化三维模型。通过正交设计及最小二乘法原理,建立了该机床机身重量、应力、变形位移的目标和约束函数。应用ANSYS有限元分析软件对其进行迭代优化,在保证机身强度和刚度的前提下,获得机身重量最轻的压力机机身结构。     

广义非线性集值混合拟变分不等式的扰动迭代算法

本文对一类广义非线性集值混合拟变分不等式进行了研究.首先,利用刘理蔚与李育强的结果,可知黄南京的结果中出现的集值映像实际上是单值的.其次,利用Siddiqi和Ansari的方法以及不动点理论,我们证明了这类混合拟变分不等式解的存在性,并给出了一个解这类混合拟变分不等式的新的扰动迭代算法.最后,讨论了这个新的扰动迭代算法的收敛判据.     

电子稳像的灰度投影三点局域自适应搜索算法

灰度投影算法是检测图像序列帧间运动矢量,实现电子稳像的关键技术之一。通过对其相关曲线的分析,基于单峰性的特征,提出了三点局域自适应搜索算法,即:在搜索宽度内均匀选取3点,计算比较其相关值,判断相关曲线梯度的变化方向,相应调整搜索参数,获得帧间运动矢量,在此基础上即可进行运动滤波和图像补偿,从而实现电子稳像。当搜索宽度为2n-1(n=1、2……且2n-1小于搜索方向上图像宽度的一半)时其运算量仅为3n,而非以往全局搜索算法的2n 1-1,从而克服了运算量大、耗时长的缺陷。该算法得到了仿真实验的验证。     

A New Optimal Iterative Algorithm for Solving Nonlinear Poisson Problems in Heat Diffusion

The nonlinear Poisson problems in heat diffusion governed by elliptic type partial differential equations are solved by a modified globally optimal iterative algorithm (MGOIA). The MGOIA is a purely iterative method for searching the solution vector x without using the invert of the Jacobian matrix D. Moreover, we reveal the weighting parameter αc in the best descent vector w = αcE + DTE and derive the convergence rate and find a criterion of the parameter γ. When utilizing αc and γ, we can further accelerate the convergence speed several times. Several numerical experiments are carefully discussed and validated the proposed method.     

基于滑动峰态算法的信号弱冲击特征提取及应用

机械故障振动信号中往往含有故障引起的弱冲击成分,冲击信号具有显著的非高斯特性,而零时滞四阶累积量即峰态能够描述信号偏离高斯分布的程度;基于峰态这一特性,本文提取一种基于滑动峰态算法的弱冲击特征提取方法,首先对原信号进行滑动峰态计算,获得一个新的峰态时间序列,然后对该峰态时间序列进行傅立叶变换,提取出信号中冲击成分的频率特征。通过强背景信号及噪声环境下弱冲击特征提取的仿真研究,证明了该方法具有很好的冲击特征提取能力。以实测齿轮断齿信号分析结果证明了该方法的有效性。     

二维不规则件优化排样的小生境遗传算法

首先采用组合矩形包络算法将二维不规则零件的排样问题转化为矩形件的排样问题;然后将遗传算法与小生境技术相结合,寻找排样件在排样时的最优次序及各自的旋转角度;最后用“最低水平线与填充算法相结合”策略的启发式排样算法实现自动排样。实例表明,该算法是有效的。     

一种强干扰下超弱水声信号自适应盲分离的快速算法

许多盲源分离算法对超弱信号收敛速度变慢甚至失效。文章提出一种算法 ,用FASTICA算法所得的分离矩阵作为一种基于输出去相关自适应盲分离算法的初始值 ,算法的收敛速度得到明显改善。算法的学习速率通过一种自适应算法选取 ,从而降低了算法收敛速度对学习步长的依赖。仿真结果表明 ,文中提出的算法对超弱信号特别有效 ,算法收敛速度大大增强。该算法可以用于分离强干扰下的弱水声信号     

A regional genetic algorithm for the discrete optimal design of truss structures

A regional genetic algorithm (R‐GA) is used for the discrete optimal design of truss structures. The chromosomes are selected from a sub‐region centred on the continuous optimum. This approach replaces genetic rebirth as previously proposed by other authors, thereby significantly reducing computational costs. As a pure discrete method, the R‐GA method does not require heuristic arguments or approximations. This makes the algorithm highly effective when buckling and slenderness constraints with scatter in the data are introduced. A large set of numerical test examples is used to illustrate the capabilities of the method. The algorithm is shown to be effective and robust, making it suitable for the optimal design of very large truss structures. Copyright © 1999 John Wiley & Sons, Ltd.     

A genetic algorithm with memory for optimal design of laminated sandwich composite panels

This paper is concerned with augmenting genetic algorithms (GAs) to include memory for continuous variables, and applying this to stacking sequence design of laminated sandwich composite panels that involves both discrete variables and a continuous design variable. The term “memory” implies preserving data from previously analyzed designs. A balanced binary tree with nodes corresponding to discrete designs renders efficient access to the memory. For those discrete designs that occur frequently, an evolving database of continuous variable values is used to construct a spline approximation to the fitness as a function of the single continuous variable. The approximation is then used to decide when to retrieve the fitness function value from the spline and when to do an exact analysis to add a new data point for the spline. With the spline approximation in place, it is also possible to use the best solution of the approximation as a local improvement during the optimization process. The demonstration problem chosen is the stacking sequence optimization of a sandwich plate with composite face sheets for weight minimization subject to strength and buckling constraints. Comparisons are made between the cases with and without the binary tree and spline interpolation added to a standard GA. Reduced computational cost and increased performance index of a GA with these changes are demonstrated.     

Improved mine blast algorithm for optimal cost design of water distribution systems

The design of water distribution systems is a large class of combinatorial, nonlinear optimization problems with complex constraints such as conservation of mass and energy equations. Since feasible solutions are often extremely complex, traditional optimization techniques are insufficient. Recently, metaheuristic algorithms have been applied to this class of problems because they are highly efficient. In this article, a recently developed optimizer called the mine blast algorithm (MBA) is considered. The MBA is improved and coupled with the hydraulic simulator EPANET to find the optimal cost design for water distribution systems. The performance of the improved mine blast algorithm (IMBA) is demonstrated using the well-known Hanoi, New York tunnels and Balerma benchmark networks. Optimization results obtained using IMBA are compared to those using MBA and other optimizers in terms of their minimum construction costs and convergence rates. For the complex Balerma network, IMBA offers the cheapest network design compared to other optimization algorithms.     

一类离散时间代数Riccati矩阵方程异类约束解的双迭代算法

本文研究在最优控制系统中遇到的离散时间代数Riccati矩阵方程(DTARME)异类约束解的数值计算问题.首先对多变量DTARME中的逆矩阵采用矩阵级数方法进行等价转化,然后采用牛顿算法求多变量DTARME的异类约束解,并采用修正共轭梯度法求由牛顿算法每一步迭代计算导出的线性矩阵方程的异类约束解或者异类约束最小二乘解,建立求多变量DTARME的异类约束解的双迭代算法.双迭代算法仅要求多变量DTARME有异类约束解,不要求它的异类约束解唯一,也不对它的系数矩阵做附加限定.数值算例表明,双迭代算法是有效的.     

求解矩形布局问题的自适应算法

矩形布局问题属于NP-Hard问题,其求解算法多为启发式算法。该文侧重于构造布局求解算法中定位函数(规则)的优化,将模拟退火算法的思想融入到遗传算法中,提出了求解矩形布局问题的自适应算法,其利用自适应交叉、变异及接收劣质解的概率等方法对定位函数中各参数进行优化。算法通过两种方式确定初始种群的数目,具有较强的适应性。在算法搜索的后期,利用差异性较大的个体进行交叉操作,从而保持种群的多样性。最后通过实例证明了该算法能够很好的应用于矩形布局问题的求解。     

双视三维重建的高精度运动参数估计方法

从两幅透视图像恢复被摄目标的三维结构是计算机视觉最基本的任务之一,其中,运动估计算法的性能决定了最终的三维重建精度。首先讨论了双视成像的基本数学模型,并介绍了几种现有运动参数估计方法的基本原理和不足。随后,基于投影误差最小判决函数,提出了用于双像运动估计的改进非线性迭代优化方法。数值仿真结果表明,在大平移小旋转角及小平移大旋转角2种运动条件下,采用文中提出的方法,运动估计精度均有所提高。此外,根据运动参数的估计值对真实目标进行三维重建实验,结果表明尺度重建误差小于2%且角度误差在3°以内。     

基于非线性最小二乘的电容层析成像图像重建算法

针对电容层析成像技术中的"软场"效应和病态问题,提出了基于非线性最小二乘算法的新电容层析成像(ECT)算法。在分析非线性最小二乘问题残量原理的基础上,给出了目标函数中二阶信息项的割线近似的校正公式,并利用Lipschitz空间连续的性质对非线性最小二乘算法的收敛性进行了证明,在此基础上探讨了ECT应用该算法的可行性。该算法满足收敛条件且重建图像误差小。仿真和实验结果表明,与LBP、Landweber和共轭梯度算法相比,对于简单流型该算法兼备成像质量高、边界均匀稳定等优点,该算法的提出为ECT图像重建算法的研究提供了一个新的思路。     

双目视觉摄像机神经网络标定方法

摄像机标定是精密视觉测量的基础。为了描述双目视觉中三维空间物点坐标和两个摄像机像面像点坐标间的非线性关系,传统的标定方法需要建立复杂的数学模型。而神经网络可以有效地处理非线性映射问题,笔者介绍了一种BP(ErrorBackPropagation)神经网络,并且为了提高网络的学习能力引入了动态因子。用相同的参考数据,将神经网络标定方法与线性标定方法比较,实验结果表明基于神经网络的双目视觉标定方法能获得较高的标定精度。     

An Optimal Multi-Vector Iterative Algorithm in a Krylov Subspace for Solving the Ill-Posed Linear Inverse Problems

An optimal m-vector descent iterative algorithm in a Krylov subspace is developed, of which the m weighting parameters are optimized from a properly defined objective function to accelerate the convergence rate in solving an ill-posed linear problem. The optimal multi-vector iterative algorithm (OMVIA) is convergent fast and accurate, which is verified by numerical tests of several linear inverse problems, including the backward heat conduction problem, the heat source identification problem, the inverse Cauchy problem, and the external force recovery problem. Because the OMVIA has a good filtering effect, the numerical results recovered are quite smooth with small error, even under a large noise up to 10%.     

A new hybrid meta-heuristic algorithm for optimal design of large-scale dome structures

In this article a hybrid algorithm based on a vibrating particles system (VPS) algorithm, multi-design variable configuration (Multi-DVC) cascade optimization, and an upper bound strategy (UBS) is presented for global optimization of large-scale dome truss structures. The new algorithm is called MDVC-UVPS in which the VPS algorithm acts as the main engine of the algorithm. The VPS algorithm is one of the most recent multi-agent meta-heuristic algorithms mimicking the mechanisms of damped free vibration of single degree of freedom systems. In order to handle a large number of variables, cascade sizing optimization utilizing a series of DVCs is used. Moreover, the UBS is utilized to reduce the computational time. Various dome truss examples are studied to demonstrate the effectiveness and robustness of the proposed method, as compared to some existing structural optimization techniques. The results indicate that the MDVC-UVPS technique is a powerful search and optimization method for optimizing structural engineering problems.