填充启发式算法的二维矩形排样问题

针对小矩形切割的二维排样问题,尤其是对玻璃或厚钢板等材料,在切割时定向一次性切割到头的排布.结合综合蚂蚁算法和模拟退火算法思想,提出了一种最低水平线与填充式算法相结合的启发式排样算法.通过对计算机上随机产生的实验数据进行模拟,实现了自动排样.实验表明,该算法提高了单次切割的材料利用率,得到较好的排样效果.     

基于遗传算法对二维天线罩瞄准误差的优化

基于物理光学法及表面积分法计算了二维相控阵天线罩的瞄准误差并利用遗传算法对瞄准误差进行优化。首先建立二维相控阵天线一罩系统的数学模型并对瞄准误差进行分析计算,并在此基础上利用遗传算法对天线罩的壁厚分布进行编码以实现对瞄准误差的优化。     

基于二维网孔互连网络的并行矩阵乘算法

矩阵乘法是数值分析领域中一种十分常用的基本运算，被广泛应用于模式识别、图像和信号处理。由于矩阵运算具有局部性、一致性的特点，特别适合用二维网孔并行计算机来实现。文章讨论了基于二维网孔互连网络的矩阵乘并行算法的实现，首先给出了一种正方网孔处理机阵列的并行算法，然后将其推广到长方网孔处理机阵列中。最后通过在LSMPP计算机的应用，证明算法是可行的、有效的。     

MPEG4编码器二维DCT变换的FPGA实现及优化

本文提出了一种适用于MPEG4视频编码系统的二维DCT的FPGA设计方案，该方案具有实时、高精度、易于FPGA实现的特点。在设计中，分别对DCT的算法及实现方法进行了分析和选择；在此基础上，对系统的结构进行了优化，提出了一种不同于传统二维DCT系统的新结构。最后对IDCT单元的运算精度进行了验证。     

基于遗传算法的二维散射中心提取研究

提出了一种基于遗传算法的雷达目标二维散射中心提取方法，并给出了适用条件，它采用CLEAN方法，将每个散射中心的提取转化为一个非线性优化问题，并利用改进的遗传算法进行优化求解。仿真结果表明，相对于传统的FFT方法和2-D Esprit方法，文中提出的二维散射中心提取方法在准确性、鲁棒性和分辨力等方面具有优势。     

计算机优化排样

文中对计算机优化排样扔算法进行了研究，从提高系统的优化程度和尽可能缩短系统的运行时间关卡别对球同零件的多件排样，提出“二步法”，将矩形模块法与启发式搜索法结合起来，并通过编程在实际应用中取得了良好的效果 。     

信号与系统仿真实验的研究

传统的实验手段无法全面的反映“信号与系统”课程中的许多基本理论,特别是非周期信号的时域与频域分析、基本运算性质、系统的设计与实现等。本文展开了计算机仿真和虚拟实验的研究,力求用形象生动的二维、三维图形表现形式,加深学生对“信号与系统”课程理论的理解。     

带残损原材料的二维优化下料问题的研究

本文将遗传算法和模拟退火算法相结合来求解二雏优化下料问题，下料件为不规则形状，原材料上带有残损，问题具有一般性。并在Windows2000平台下，用Matlab实现上述算法。通过实例验证了该算法的有效性。     

用二维函数分析彩色电视信号

数字计算机可用于处理NTSC和PAL彩色电视信号。本文介绍了Fourier图形和Walsh图形。用二维Fourier变换和二维Walsh变换处理NTSC及PAL信号。     

对用Chart控件的SetData函数绘制曲线图和散点图的研究与实现

本文主要介绍了Chart控件的一些基本属性，在VC 中运用计算机图形学原理绘制二次曲线的一些方法以及如何使用Chart控件的SetData函数进行二雄图形的绘制，并就用Chart控件绘图的精度问题进行了定量分析。     

基于遗传算法的不规则物体布局求解方法研究

通过对不规则物体布局特点的分析,依据遗传算法的基本思想,提出一种基于遗传算法的不规则物体布局求解算法.本算法选择合适的编码方法、遗传算子和合适的适应性度函数,仿真实验表明,该算法具有收敛速度快,解决早熟现象,能够在较短时间内获得较佳的布局方案.     

Application of genetic algorithms and simulated annealing techniquein optimising the aperture distributions of antenna array patterns

Simulated annealing and genetic algorithms are used for finding optimum excitations for patterns with null-filling. These methods have the advantage that the optimum aperture distribution with a minimal variation between excitations of adjacent elements is found without searching the entire solution space. A comparison between the performance of both methods shows that genetic algorithms are faster than simulated annealing, for this problem     

Radial EBG cell layout for GPS patch antennas

A novel radial layout for mushroom-like electromagnetic-bandgap (EBG) cells surrounding a printed circularly-polarised patch antenna is proposed. Two radial EBG configurations surrounding a circular patch are compared to a reference patch on a conventional ground plane of the same dimension. The radial shape and displacement of the EBG cells around the patch offers improvements in terms of gain and axial-ratio compared to the reference antenna and is more suitable for circular geometries compared to conventional Cartesian layouts. In particular, the distance between the patch and the surrounding EBG cells is independent of the cell period, which can be arbitrarily chosen, and the overall layout offers footprint reduction.     

基于贪心遗传算法求解0-1背包问题

在解决0-1背包问题中,将贪心算法和遗传算法相结合,提出了贪心遗传算法。通过算法构造出更优的新算子,与原有算子相比,既加快了算法的收敛速度,又克服了传统方法容易陷入局部最优的特点,提高了搜索效率。通过计算机仿真试验结果表明,贪心遗传算法相比普通的遗传算法具有更好的近似解,充分证明了贪心遗传算法来求解背包问题的有效性和实用性。     

天线布局优化仿真研究

随着车载无线系统上装无线设备电磁环境日益复杂,设备间电磁干扰日益严重,采用仿真技术进行天线布局优化可以有效减小设备间干扰。本文分析了影响车载天线系统天线布局的主要因素,得出天线优化布局的优化目标为天线间的耦合度和方向图失真度,建立了天线布局优化模型,采用改进的遗传算法对车顶天线布局进行优化设计,在电磁兼容设计初期得出粗略的最佳布局方案,使其满足电磁兼容性能要求,降低了天线布局设计的难度,并设计了电磁兼容优化仿真软件,实现了车载系统的优化布局仿真,达到工程实际要求。     

Multiuser Detection Based on Adaptive LMS and Modified Genetic Algorithm in DS-CDMA Communication Systems

In this paper, we present an efficient evolutionary algorithm for the multi-user detection (MUD) problem in direct sequence-code division multiple access (DS-CDMA) communication systems. The optimum detector for MUD is the maximum likelihood (ML) detector, but its complexity is very high and involves an exhaustive search to reach the best fitness of transmitted and received data. Thus, there has been considerable interest in suboptimal multiuser detectors with less complexity and reasonable performance. The proposed algorithm is a combination of adaptive LMS Algorithm and modified genetic algorithm (GA). Indeed the LMS algorithm provides a good initial response for GA, and GA will be applied for this response to reach the best answer. The proposed GA reduces the dimension of the search space and provides a suitable framework for future extension to other optimization algorithms. Our algorithm is compared to ML detector, Matched Filter (MF) detector, conventional detector with GA; and Adaptive LMS detector which have been used for MUD in DS-CDMA. Simulation results show that the performance of this algorithm is close to the optimal detector with very low complexity, and it works better in comparison to other algorithms.     

Design of non-uniform circular antenna arrays for side lobe reduction using the method of genetic algorithms

A design problem of non-uniform circular antenna arrays for maximal side lobe level reduction with the constraint of a fixed beam width is dealt with. This problem is modeled as a simple optimization problem. The method of genetic algorithms is used to determine an optimum a set of weights and antenna element separations that provide a radiation pattern with maximal side lobe level reduction with the constraint of a fixed beam width. The effectiveness of genetic algorithms for the design of non-uniform circular arrays is shown by means of experimental results. Experimental results reveal that design of non-uniform circular antenna arrays using the method of genetic algorithms provides a considerable side lobe level reduction with respect to the uniform case.     

Properties of optimum binary message-passing decoders

We consider a class of message-passing decoders for low-density parity-check (LDPC) codes whose messages are binary valued. We prove that if the channel is symmetric and all codewords are equally likely to be transmitted, an optimum decoding rule (in the sense of minimizing message error rate) should satisfy certain symmetry and isotropy conditions. Using this result, we prove that Gallager's Algorithm B achieves the optimum decoding threshold among all binary message-passing decoding algorithms for regular codes. For irregular codes, we argue that when the nodes of the message-passing decoder do not exploit knowledge of their decoding neighborhood, optimality of Gallager's Algorithm B is preserved. We also consider the problem of designing irregular LDPC codes and find a bound on the achievable rates with Gallager's Algorithm B. Using this bound, we study the case of low error-rate channels and analytically find good degree distributions for them.     

An Improved Genetic Algorithm with Quasi-Gradient Crossover

The convergence of genetic algorithm is mainly determined by its core operation crossover operation. When the objective function is a multiple hump function, traditional genetic algorithms are easily trapped into local optimum, which is called premature conver- gence. In this paper, we propose a new genetic algorithm with improved arithmetic crossover operation based on gradient method. This crossover operation can generate offspring along quasi-gradient direction which is the Steepest descent direction of the value of objective function. The selection operator is also simplified, every individual in the population is given an opportunity to get evolution to avoid complicated selection algorithm. The adaptive mutation operator and the elitist strategy are also applied in this algorithm. The case 4 indicates this algorithm can faster converge to the global optimum and is more stable than the conventional genetic algorithms.     

一种新的区间-遗传算法

针对传统区间优化算法求解高维问题耗时的缺点,本文将区间算法和遗传算法进行融合,给出了一种区间-遗传算法,该算法保留了传统区间优化算法简单、对问题本身信息要求不高的优点.重要的是在每次迭代中区间算法为遗传算法的搜索提供可靠区域,同时遗传算法为区间算法的区间分裂提供了一个方向、为区间删除给出了问题全局最优解的一个上界.最后给出了算法的收敛性证明,数值实验表明该算法相比传统区间优化算法有较高执行效率.