Sudoku

H=CIRCLE(CENTER,RADIUS,NOP,STYLE) This routine draws a circle with center defined as a vector CENTER, radius as a scaler RADIS. NOP is the number of points on the circle. As to STYLE, use it the same way as you use the rountine PLOT. Since the handle of the object is returned, you use routine SET to get the best result.

The code is LOW ENERGY ADAPTIVE CLUSTERING HIERARCHY(LEACH)protocol for wireless sensor network. it is an energy efficient protocol.

By using these matlab codes a simple BPSK modulation can be implemented. The format used is Polar NRZ

于群《MATLAB/Simulink电力系统建模与仿真》课本+仿真模型和代码+matpower及其使用手册(In group " MATLAB/Simulink power system modeling and simulation" textbook+ simulation model and code+matpower and use manual)

Curvelet变换是最近图像处理较新的一种多尺度几何变换算法，有详细的快速变换fdct_wrapping的matlab代码(Curvelet transform is the latest image processing a multiscale geometric transform algorithm is relatively new, there is a rapid transformation of fdct_wrapping with the matlab code)

fastica用于信号处理系统的源码，希望大家多分析多学习(FastICA for signal processing systems source code, I hope everyone more and more analysis of learning)

本书主要讲解了MATLAB语言常用算法程序集清晰版，对于初学者用处很大(This book explains the MATLAB language commonly used algorithm for assembly clear version, has proved very useful for beginners)

雷达通信系统的模糊函数的基于线性函数的matlab仿真(Radar system of communication function of fuzzy linear function based on the matlab simulation )

Matlab中的高光谱图像中的端元提取算法(An algorithm for the extraction of the end elements in hyperspectral images in MATLAB by Liuliu)

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)