cec2006

说明：   实 现 Cholesky(Cholesky)

数字信号处理在Matlab V4上的应用，纯英文书，是1997年的老书了，为PWS出版公司出版。与国内的薛年喜版《MATLAB在数字信号处理中的应用》不同，在matlab的入门上介绍不多，需要读者较熟悉matlab。(The Application of Digital Signal Processing in the Matlab V4,published by PWS publishing company in 1997.Compared with the Mr.Xue s version , there is an succinct introductory course in matlab,so that readers should know MATLAB well .)

给出了三站无源雷达对空中目标定位的精度分析.以几何稀释精度(GDOP)作为精度的指标.(Analysis gives a three-station passive radar for air target positioning accuracy. Geometric dilution of precision (GDOP) as an indicator of the accuracy.)

说明：  第四章 MATLAB 图形对象操作 4.1 图形对象的属性 4.2 图形对象句柄的获取 4.2.1 对象创建时获取 4.2.2 层次关系来获取 4.2.3 当前对象的获取 4.2.4 根据对象属性值的获取 4.3 图形对象句柄的删除与判断 4.3.1 句柄的删除 4.3.2 句柄的判断 4.4 图形对象属性值的获取与设置 4.4.1 图形对象属性值的设置 4.4.2 图形对象属性值的获取 4.4.3 用户缺省值的操作 4.5 图形对象的其它操作 4.5.1 figflag 函数 4.5.2 findfigs 函数 4.5.3 copyobj 函数 4.5.4 capture 函数 4.5.5 refresh 函数 4.5.6 saveas 函数 4.5.7 hgload 函数和 hgsave 函数 4.5.8 newplot 函数 (Chapter IV of MATLAB graphic objects to operate the properties of graphic object 4.1 graphic object handle 4.2 Access 4.2.1 object created when the relationship between the level of access to 4.2.2 to get 4.2.3 to obtain the current object under the object attribute value 4.2.4 Access 4.3 graphic object with the judge handles delete delete 4.3.1 handles 4.4 judgment 4.3.2 Handle Graphics object attribute values to obtain and set the target attribute value 4.4.1 graphics settings 4.4.2 graphic object attribute values to obtain 4.4 .3 user operation 4.5 Default graphic object 4.5.1 figflag other operations function 4.5.2 findfigs function 4.5.3 copyobj function 4.5.4 capture function 4.5.5 refresh function 4.5.6 saveas function 4.5.7 hgload function and 4.5.8 newplot function hgsave function)

静止无功补偿器部分程序，基于模块化设计，实现无阻尼控制的SVC功能。(Static var compensator part of the program，Based on modular design, the SVC damping control function.)

实现多输出的支持向量机回归，不需要对每一个输出都进行函数回归(Multi-output support vector machine regression，Each output does not need to be a function of the regression)

矩形排样的剩余矩形优化算法。在matlab中的实现。(The rectangle layout of the remaining algorithm, MATLAB optimization and efficient use of raw materials )

MATLAB的一些例程，很好很实用。一百例(MATLAB some routines, good practical. 100 cases)

介绍如何用matlab语言解决最优化问题(Describes how to solve optimization problems by matlab)

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm.)