ACS3-1

这是matlab入门的相关重要例程,对接触不久的朋友非有用哈.(This is the relevant entry-matlab important routines, Friend of the near contact of non-useful Kazakhstan.)

主要描述的是平面电磁波的电磁散射问题，适合搞电磁计算的科研人员等(This guide provides a brief reference to the Graphical User Interface (GUI) that implements the propagation of a TE (Transverse Electric)/TM (Transverse Magnetic) plane wave through a multilayered structure of media with different electromagnetic characteristics. The incident wave is a TE/TM plane wave in the the zy plane (sinusoidal regime with temporal convention ejωt ), traveling from+z to-z. )

BP网络的MATLAB工具箱的实现。。 ——Bpnet(BP network MATLAB toolbox implementation. .- Bpnet)

Matlab source code for EESAA research paper.

这是关于二自由度直升机模型的前向控制和反馈控制的simulink仿真模型(This is the simulink simulation model helicopter model before about two degrees of freedom to control and feedback control)

Matlab程序，实现了一种新的色彩白平衡算法。 针对物体在有色光源照射下呈现偏色的现象,提出一种改进的LoG边缘自动白平衡算法。该算法在YCbCr空间的Cb和Cr分量上同时利用LoG算子提取边缘,利用LoG边缘具有零交叉特性直接得到边缘两侧的像素。为了避免占主导的彩色纹理造成干扰,利用白色区域的偏色信息进行边缘抑制。利用得到彩色边缘对原图的偏色进行有效的估计,最后计算三颜色通道的增益并进行白平衡。对大量图片进行了实验,结果表明该算法对不同色光照射下的图像均能很好地进行白平衡,同时与多种白平衡算法的对比实验表明该算法适应面广,性能良好。 (Matlab program implements a new color white balance algorithms.)

convolutional coding matlab仿真代码，仅供参考(convolutional coding matlab simulation code, for reference only)

窗函数法数字滤波器设计，包括基本的六种窗函数，内有一份word实验报告，适合信号分析初学者学习(Window function digital filter design, including the six basic window function, which has a word test report, suitable for beginners to learn signal analysis)

蕞优分组周游路线问题是一类物流智能调度问题，是众多的计算难度极大的组合爆炸问题之一。自从运输问题最早是由Hitchcock在1941年提出的[2][4]后，人们对这一类问题给予了极大的关注并进行了大量的研究，提出了有效解决问题的优化算法——单纯形法的变形[2]。但由于问题规模的扩大，纯数学方法在允许的时间和空间上都很难找到问题的最优解，于是人们开始转向寻找问题的近似最优解，遗传算法以其在求解最优化问题中的独特的自组织性、自适应性很快进入人们的视野。 经典的遗传算法对于求解多目标的NP完全性问题非常有效，但对于有多个限制条件的多目标最优化问题缺显得有点力不从心，很难得到稳定度较高、收敛较快的解。本文提出的双层遗传算法模型给这一类问题提供了一个很好的解决方法，虽然建模条件限制了描述的问题的通用性，有待推广，但它能有效利用问题的领域知识，提高了求解效率，保证了解的可行性和最优性，算法思想极具推广潜力，可在其它物流智能调度问题求解算法设计中借鉴。(The most optimal packet travel route problem is a kind of intelligent logistic scheduling problem is one of combinatorial calculation difficult problem many. Since the transportation problem was first proposed by Hitchcock in 1941 after the [2][4], the people of this class of problems given great attention and made a lot of research, the deformation of [2] optimization, simplex method algorithm is effective to solve the problem of. But due to the expansion of the scale of the problem, the pure mathematical methods in the allowed time and space are very difficult to find the optimal solution of the problem, so people begin to turn to the approximate optimal solution for the problem, genetic algorithm in solving optimization problems with its unique in the self-organizing, adaptive soon entered people s field of vision. Very effective classical genetic algorithm for solving multi-objective NP complete problems, but for the multi-objective optimization problem with multiple constraints. I)

说明：  simple shoortest path