yichuan

该程序是用matlab开发的人脸识别程序，应用的方法是K_L变换(The program is the development of face recognition matlab program, the application method is to transform K_L)

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 )

能实现水平集演化，输入图片是已经经过前期处理的分割后的二值图。(These programs can reallize LevelSet evolution .The input image must be a Binary image.)

说明：  凸优化程序包，包含各种凸优化算法,可供方便调用.(Convex optimization package, contains a variety of convex optimization algorithm, for convenience call.)

The program is for pseudocolor image processing, it can convert a grayscale image to color. The color may not be accurate but quite useful for certain applications.

半定规划内点法数据整理交直流系统统一无功优化算法，系数矩阵的确定。(Interior point method for semidefinite programming data collation AC and DC systems unified reactive power optimization algorithm to determine the coefficient matrix.)

modular multi level converter

一些强化学习方面的论文，很有用的，有着具体的例子，和算法流程和思路，希望对大家有所帮助(reinforcementlearing)

说明：  用于支持向量机方法识别光谱，是很好的光谱识别程序(For support vector machine method to identify spectrum, good spectral identification procedures)

分段卷积算法实现，并与基于DFT的线性卷积比较(Piecewise convolution algorithm, and compared with DFT-based linear convolution)