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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 )

matlab/simmatlab/simulinkSfunctionC文件例子源码ulinkSfunctionC文件例子源码(matlab/simmatlab/simulinkSfunctionC paper documents examples of ulinkSfunctionC example source code)

说明：  车型轮廓提取 用于车型识别中的图像预处理(Contour extraction model)

jis0208日文编码数组,使用时将高字节减去0X20,低字节减去0X20,(jis0208 Japanese encoded array, use the high byte minus 0X20, low byte minus 0X20,)

Genetic algorithm _optimization matlab program

说明：  For partial shading of PV system.

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基于AR模型的burg算法，根据100年间每年12个月记录到的太阳黑子出现次数的平均值求太阳黑子的活动周期。（matlab程序和实验报告）(Burg algorithm based on AR model, according to 100 years, 12 months per year sunspot record to appear and sunspot activity cycle of the average number of times. The (matlab Programs and lab reports))

quaternion example and application

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