20130809

独立成分分析（Independent Component Analysis, ICA）是近年来发展起来的一种有效的盲分离技术，最早是由法国学者Herault和Jutten于1986年提出。ICA方法的提出最初是用来解决“鸡尾酒会”问题，其过程可以归纳为，在源信号与传输通道参数均未知的情况下，仅根据源信号的统计特性，出现测信号恢复出源信号。ICA分析的关键在于根据一定的优化准则建立描述输出信号独立程度的优化判据，即目标函数，并设计相应的优化算法，寻求最优的分离矩阵，使得输出信号中各分量尽可能相互独立。采用ICA方法对信号进行盲分离时，可避免过多地受大能量噪声成分的影响，将部分小能量信号源识别出来。随着ICA技术的不断发展，目前ICA技术已经广泛应用于语音增强、音频识别、通信、医学信号处理、金融数据挖掘、图像消噪、数字水印、遥感等领域，并取得了一定的研究成果。(Independent Component Analysis (ICA) Component ini order, developed in recent years is a kind of effective separation technology, originally from French scholars Herault and Jutten in 1986. The proposed method is initially ICA to solve the "cocktail" problem, the process can be divided into, in the source signal transmission channels and in the case of unknown parameters according to the source of the signals, and the statistical characteristics of recovering the source signal. According to the analysis of the ICA key lies in the establishment of optimal criteria described the output signal of the independent, objective function optimization criterion, and the corresponding optimization algorithm, the optimum )

Numerical solution of the state equations

This toolbox provides tools to create sophisticated MATLAB graphical user interfaces that resize gracefully. The classes supplied can be used in combination to produce virtually any user interface layout.

Matlab ebook circuit simulation

说明：  采用均值聚类的方法找出径向基函数中心，并对训练数据展开预测(Mean clustering method is used to find the center of radial basis function and forecast the training data.)

说明：  在matlab中，以simulink为主要工具介绍了系统仿真方法与技巧，包括连续系统、离散系统、随机输入系统和负数系统的仿真。(In matlab in order to simulink introduced as the main tool for system simulation methods and techniques, including continuous systems, discrete systems, stochastic systems and the negative input of the simulation system.)

层次分析（AHP）/网络分析（ANP)Analytic Hierarchy Process是一种十分实用的决策方法。 是对一些较为复杂、较为模糊的问题作出决策的简易方法，它特别适用于那些难于完全定量分析的问题 num:包括目标层和方案层的总层数 g:行向量（各层准则数量，包括目标层（第一层）和方案层（最后一层））。 w：返回值w是最后决策的方案层的权重，根据输出选择最佳方案 在输入矩阵时请加‘[]’号，否则会出现语法错误。 调运方式：w=hierarchy(num,g)( Analytical Hierarchy (AHP)/Network Analysis (ANP) Analytic Hierarchy Process is a very practical approach to decision making. Is the easy way of making some of the more complex, more ambiguous issues make it particularly difficult for those who complete quantitative analysis of the problem num: The total number of layers including the target layer and the solution layer g: row vector (layers Guidelines number, including the target layer (first layer) and program level (the last level)). W: w The return value is the right solution layer of the final decision of the heavy, choose the best option based on the output when the input matrix please add ' []' No, there would be a syntax error. Transporting way: w = hierarchy (num, g))

说明：  采用K- means 算法和FCM 算法实现对47 个城市竞争力的聚类分析(Using K-means algorithm and FCM algorithm to achieve the competitiveness of 47 cities in the cluster analysis)

说明：  kruskal 算法程序 解决最短路径问题 (kruskal shortest path algorithm to solve the issue of procedures)

说明：  信息隐藏算法（转载）武汉大学出版处王丽娜教授等书中源码(Information hiding algorithm (reproduced))