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基于核分析的多类分类器，支持向量机的多类分类，适合研究学习，欢迎同行下载(Kernel-based analysis of the many types of classifier, support vector machine multi-category classification, suitable for study of learning, welcomed the peer download)

这个程序是基于ＭＡＴＡＬＢ平台实现的，由于本程序是自己编的，所以还有不足的地方如那位大侠有好的建议请提出(This procedure is based on the MATALB platform, as a result of this process is allocated its own, so there are less than places such as the heroes who have put forward good suggestions, please)

说明：  此为对于均匀阵列的MUSIC算法的源代码，希望对大家有用(this a uniform array for the MUSIC algorithm source code, we want to help!)

书籍 《最优化方法及其matlab程序设计》 作者马昌凤 matlab源代码(Books optimization methods and Matlab programming Convergent Descend Matlab source code)

PLSA EM演算法，用於文本與字詞之間的矩陣工具，測量其相似度(PLSA EM algorithm for the matrix between the text and words tool to measure the similarity)

多项式和非多项式曲线拟合，MATLAB的经典案例 (Polynomial and non polynomial curve fitting)

元胞自动机的大部分程序，包括元胞自动机生成sierpinski直角垫片 ，在六边形的元胞自动机上模拟单粒子运动,算法是基于FHP规则.以及元胞自动机模拟地球卫星的云图 ，元胞以固定的概率向相邻的4个元胞扩散 zz问题，元胞自动机模拟地球卫星的云图 ，以及生命游戏，机器人等程序(Cellular automata most programs, including cellular automata generate sierpinski Cartesian pads, analog single particle motion in the hexagonal cellular automata, FHP is based on rules. Well as cellular automata simulation Earth satellite imagery , cellular fixed probability to four adjacent cellular proliferation zz problems, cellular automata simulation Earth satellite imagery, as well as Game of Life, robots and other procedures)

生成调制信号数据集 信号集包括2ASK，2PSK，2FSK，4ASK，4PSK，4FSK，8ASK，8PSK，8FSK，16QAM，64QAM，信号比范围-20db至18dB，调制到中频。 信号参数 符号率fb：1e3 载波频率fc：2e3 采样频率fs：64e3 信号频道：awgn，rayleigh(Generating Modulation Signal Data Set Signal sets include 2ASK, 2PSK, 2FSK, 4ASK, 4PSK, 4FSK, 8ASK, 8PSK, 8FSK, 16QAM, 64QAM, signal ratio range - 20 dB to 18dB, modulated to intermediate frequency.)

关于直流电机的空载特性的matlab仿真，采用的是样条插值算法对曲线进行拟合，初学者可以改为其他拟合方式看结果如何(With regard to the no-load characteristics of DC motor matlab simulation, using the spline interpolation algorithm, beginners can be fitted into other ways to see the results)

说明：  近红外光谱分析中要从复杂的信息中有效地提取相关信息建立可靠的模型，选择的训练集要具有较好的代表性。目前．样本的选择方法主要包括random sampling(RS)，Kennard—Stone(KS)．sample set partitioning based on joint x-y distance(SPXY)等方法 。(selecting a representative subset in NIR data using SPXY， the random sampling，and Kennard—Stone methods )