Adaboost

多目标优化 相对传统多目标优化方法, PSO在求解多目标问题上具有很大优势。首先, PSO的高效搜索能力有利于得到多目标意义下的最优解 其次, PSO通过代表整个解集的种群按内在的并行方式同时搜索多个非劣解,因此容易搜索到多个Pareto 最优解 再则, PSO的通用性使其适合于处理所有类型的目标函数和约束 另外, PSO 很容易与传统方法相结合,进而提出解决特定问题的高效方法。就PSO 本身而言,为了更好地解决多目标优化问题,必须解决全局最优粒子和个体最优粒子的选择问题(Compared with the traditional multi-objective optimization of multi-objective optimization method, PSO in solving multi-objective problem has a great advantage. First, PSO is conducive to the efficient search capabilities are more objective sense of the optimal solution Secondly, PSO representative of the entire solution set through the population by way of the inherent parallel search multiple non-inferior solution, and this can easily search for the most number of Pareto optimal solution Furthermore, PSO' s versatility make it suitable for handling all types of objective function and constraints addition, PSO is easy to integrate with the traditional method, and then propose an efficient way to solve specific problems. The PSO itself, in order to better address the multi-objective optimization problems, the need to address the global best particle and the individual selection of the optimal particle)

用matlabr2009编程实现神经网络模糊聚类算法，采用cell工具把整个程序分为以下几个部分(Programming neural network with matlabr2009 fuzzy clustering algorithm, using cell tools to the entire program is divided into the following sections)

很强大的3d模式求解程序，可以求解各种结构的模式分布(3D mode solver,)

bestEbook : Programming in MATLAB ebook

Double side band-suppressed carrier (DSB-SC)simulation on simulnik-matlab.

包含了许多马蹄兰的用法，为大家提供了一个学习matlab的很好工具。(Contains many Calla usage, provide a good learning tool for matlab.)

matlab 6.0 时尚百例的21-30的代码，基本函数的应用(Fashion matlab 6.0 code 21-30 of 100 cases, the basic function of the application)

说明：  matlab中对任意figure中的数据图像部分放大，源程序中附有随机波形的例子。(matlab figure in the data for any part of the image magnification, the source program with a random waveform example.)

利用夹角余弦距离进行样本数据分类。实现步骤主要分为以下两部分：a、待测样品X与训练集里每个样品Xi的距离采用夹角余弦距离公式计算。b、循环计算待测样品和训练集中各已知样品之间的距离，找出距离待测样品最近的已知样品，该已知样品的类别就是待测样品的类别。(Using the sample data classification Angle cosine distance.Implementation steps are divided into the following two parts: a, sample under test with each of the samples in the training set X Xi distance using the included Angle cosine distance formula.B, loop calculation under test samples and the distance between the known samples training focus, find out the known closest to the sample under test samples, the samples of known category is the category of the sample under test.)

这是本人下载和编译过的关于大津法二值化的matlab代码，效果比较好，可以作为分割的有效辅助(This is, I downloaded and compiled on the Otsu binarization method of matlab code, the effect is better, can be used as an effective auxiliary partition)